
## Full Description
We have a urgent requirement for a Generative AI Consultant to be based in Dubai for a major IT vendor.

Key Responsibilities:

- Strategise and implement generative AI use-cases and transformation models across multiple industries.

- Lead a specialised team in crafting and executing a customer-focused generative AI roadmap, with an emphasis on technical governance.

- Disseminate key service updates and compliance guidelines to internal and external stakeholders.

- Regularly attend customer site meetings and produce periodic reports to update customers on account status, risk mitigation, and service activities.

- Coordinate troubleshooting efforts across support, account, and field service teams for efficient problem-solving.

Qualifications:

- Bachelor's degree in Computer Science, Information Technology, or a related field (Master's degree preferred).

- Extensive expertise in Generative AI methodologies, complemented by over 5 years of hands-on experience in AI and customer-facing roles.

- Proficiency in data classification, inferencing, training model fine-tuning, and a proven track record of leading C-level customer discussions to create strategic roadmaps.

- In-depth knowledge of model selection, data preparation, and tooling ecosystems in Generative AI, including a strong understanding of Kubernetes and MLOps.

- Outstanding customer engagement skills, including the ability to build trust, plan workshops, and communicate persuasively across all levels within Dell Technologies and external partner organizations.

- Demonstrated experience in client-facing service delivery, with a commitment to adhering to project methodologies and contractual obligations. Onsite availability during customer workshops is essential.

• *Salary**: AED16,000.00 - AED30,000.00 per month

Ability to commute/relocate:

- Dubai: Reliably commute or planning to relocate before starting work (required)




## Full Description
Part-Time Trainer for Artificial Intelligence

05/12/2025

One of the leading and fast emerging Institutions from Malta, Europe offering a wide range of industry driven and job-oriented programme is inviting job application for part-time faculty for its Dubai Campus for the following discipline:

Job Description: Artificial Intelligence—Foundational Level (20-Hour Training Program)

Role Overview• Deliver a foundational 20-hour training program on Artificial Intelligence for beginner-level learners, 2-3 hours a day afternoon.

• Focus on practical, application-based content that enables students to use AI tools to boost productivity, creativity, and efficiency.

Key Responsibilities

• Conduct clear, engaging training sessions introducing AI concepts in simple and practical ways.

• Teach hands-on use of AI tools for writing, research, presentations, image generation, task automation, and productivity improvement.

• Develop lesson plans and training materials tailored for total beginners with no technical background.

• Demonstrate real-life use cases of AI in work, education, and daily productivity.

• Provide guided practice, demonstrations, and small, achievable projects for learners.

• Assist students individually to ensure they understand how to apply AI tools effectively.

• Encourage active participation through interactive activities, group tasks, and practical exercises.

• Monitor learner progress and give constructive feedback.

• Assess learning outcomes through assignments, quizzes, or practical evaluations.

• Maintain a supportive, motivating, and safe learning environment.

Skills & Competencies

· Strong understanding of modern AI tools and platforms (e.g., ChatGPT, image generators, summarization tools, AI productivity apps).

· Ability to simplify complex AI concepts for beginners.

· Experience in hands-on, application-based training or instruction.

· Excellent communication, presentation, and facilitation skills.

· Creativity in designing practical exercises and real-world examples.

· Patience and adaptability when teaching learners of diverse skill levels.

Preferred Qualifications

· Experience as an AI trainer, digital skills instructor, or tech facilitator (preferred).

· Familiarity with Generative AI, machine learning basics (non-technical), and AI ethics.

· Background in computer science, education, digital technologies, or related fields (not mandatory if skilled).

Job Type: Part-time




## Full Description
I am hiring for AWS Data Engineer

Location: Glasgow 2–3 days per weekly Onsite

Job Description

We are looking for an experienced AWS Data Engineer with strong hands-on coding skills and expertise in designing scalable cloud-based data solutions. The ideal candidate will be proficient in Python, PySpark, and core AWS services, with a strong background in building robust data pipelines and cloud-native architectures.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL workflows using AWS services.

• Implement data processing solutions using PySpark and AWS Glue.

• Build and manage infrastructure as code using CloudFormation.

• Develop serverless applications using Lambda, Step Functions, and S3.

• Perform data querying and analysis using Athena.

• Support Data Scientists in model operationalization using SageMaker.

• Ensure secure data handling using IAM, KMS, and VPC configurations.

• Containerize applications using ECS.

• Write clean, testable Python code with strong unit testing practices.

• Use GitLab for version control and CI/CD.

Key Skills

Python, PySpark, S3, Lambda, Glue, Step Functions, Athena, SageMaker, VPC, ECS, IAM, KMS, CloudFormation, GitLab



## Qualifications
* 15+ years in data engineering, data architecture, or analytics leadership, including senior-level team management
* Several years of experience deploying AI/ML solutions within a SaaS or enterprise technology environment
* Demonstrated ability to lead teams spanning data engineering, AI/ML, analytics, and platform operations
* Hands-on experience with advanced prompting and LLM-based application development
* Deep understanding of machine learning, statistical modeling, and applied predictive analytics
* Cloud: Azure, AWS, or GCP
* Data platforms: Databricks, Snowflake, Synapse, BigQuery
* Orchestration: dbt, Airflow, Data Factory, Fivetran
* Analytics: Power BI, Tableau, Looker
* AI/ML frameworks: OpenAI, Azure AI, Anthropic/Claude, Bedrock
* Monitoring: Application Insights, Grafana, New Relic
* Experience establishing governance standards for data quality, privacy, ethics, and AI lifecycle management
* Strong grasp of CI/CD practices, DevOps tooling, and engineering productivity metrics
* Familiarity with Agile delivery processes and compliance frameworks such as SOC, PCI, or GDPR
* Excellent communication, leadership, and cross-functional collaboration skills
* A blend of technical depth and strategic insight, the ability to inspire engineering teams, and a passion for building systems that turn raw data and AI capabilities into business-defining outcomes
* You balance innovation with reliability, thrive in complex environments, and elevate everyone around you
## Responsibilities
* We’re seeking a Vice President of Data & AI to define and execute a company-wide strategy that elevates product intelligence, operational efficiency, and enterprise decision-making
* This role blends vision, architecture, and hands-on leadership
* You'll design the next generation of AI-driven capabilities, unify data systems across the business, and guide engineering teams in building scalable, reliable, and ethically responsible solutions
* Your work will directly influence product innovation, internal analytics, automation, and strategic insights across a wide range of departments
* Shape and execute a holistic data and AI strategy that strengthens product capabilities and internal intelligence
* Architect AI-powered features that support automation, predictive insights, anomaly detection, and other advanced use cases
* Develop refined prompting, tuning, and interaction methodologies for large language models and generative AI systems
* Build sophisticated machine learning and statistical models that support reliable forecasting and data-driven decisioning
* Craft clear, meaningful analytical stories through data visualizations and executive-ready insights
* Partner with product and design teams to weave data and AI seamlessly into customer-facing workflows
* Develop internal analytics solutions supporting pipeline management, revenue insights, customer health, operational trends, and more
* Assess and recommend emerging AI technologies and tools to enhance productivity and scalability
* Lead the creation of an integrated data platform connecting sources across sales, finance, operations, support, and product telemetry
* Establish a mature governance framework emphasizing responsible AI, transparency, and risk mitigation
* Deliver self-service data assets, curated models, and dashboards for analysts and business teams
* Define engineering standards across architecture, security, quality, and operational readiness
* Create and maintain a long-term roadmap covering platform evolution, technical debt reduction, and modernization initiatives
* Collaborate closely with DevOps and infrastructure teams to ensure stable, high-performance production operations
* Build, lead, and develop a distributed team of data engineers, machine learning engineers, analysts, and technical managers
* Track performance metrics, delivery progress, and organizational impact across all data and AI initiatives
* Act as a strategic advisor to senior technology and product leadership on emerging patterns, platforms, and industry direction

## Full Description
VP of Data Science and AI | $200K - $240K | Hybrid | Atlanta, GA

Are you a forward-thinking technical leader who excels at shaping data ecosystems and transforming AI concepts into real, measurable business value? We’re seeking a Vice President of Data & AI to define and execute a company-wide strategy that elevates product intelligence, operational efficiency, and enterprise decision-making.

This role blends vision, architecture, and hands-on leadership. You'll design the next generation of AI-driven capabilities, unify data systems across the business, and guide engineering teams in building scalable, reliable, and ethically responsible solutions. Your work will directly influence product innovation, internal analytics, automation, and strategic insights across a wide range of departments.

If you thrive in high-impact environments, love building modern data platforms, and enjoy mentoring talented technical teams, this is an opportunity to lead with both creativity and precision.

Key Responsibilities

• Shape and execute a holistic data and AI strategy that strengthens product capabilities and internal intelligence.

• Architect AI-powered features that support automation, predictive insights, anomaly detection, and other advanced use cases.

• Develop refined prompting, tuning, and interaction methodologies for large language models and generative AI systems.

• Build sophisticated machine learning and statistical models that support reliable forecasting and data-driven decisioning.

• Craft clear, meaningful analytical stories through data visualizations and executive-ready insights.

• Partner with product and design teams to weave data and AI seamlessly into customer-facing workflows.

• Develop internal analytics solutions supporting pipeline management, revenue insights, customer health, operational trends, and more.

• Assess and recommend emerging AI technologies and tools to enhance productivity and scalability.

• Lead the creation of an integrated data platform connecting sources across sales, finance, operations, support, and product telemetry.

• Establish a mature governance framework emphasizing responsible AI, transparency, and risk mitigation.

• Deliver self-service data assets, curated models, and dashboards for analysts and business teams.

• Define engineering standards across architecture, security, quality, and operational readiness.

• Create and maintain a long-term roadmap covering platform evolution, technical debt reduction, and modernization initiatives.

• Collaborate closely with DevOps and infrastructure teams to ensure stable, high-performance production operations.

• Build, lead, and develop a distributed team of data engineers, machine learning engineers, analysts, and technical managers.

• Track performance metrics, delivery progress, and organizational impact across all data and AI initiatives.

• Act as a strategic advisor to senior technology and product leadership on emerging patterns, platforms, and industry direction.

Required Skills & Experience

• 15+ years in data engineering, data architecture, or analytics leadership, including senior-level team management.

• Several years of experience deploying AI/ML solutions within a SaaS or enterprise technology environment.

• Demonstrated ability to lead teams spanning data engineering, AI/ML, analytics, and platform operations.

• Hands-on experience with advanced prompting and LLM-based application development.

• Deep understanding of machine learning, statistical modeling, and applied predictive analytics.

• Cloud: Azure, AWS, or GCP

• Data platforms: Databricks, Snowflake, Synapse, BigQuery

• Orchestration: dbt, Airflow, Data Factory, Fivetran

• Analytics: Power BI, Tableau, Looker

• AI/ML frameworks: OpenAI, Azure AI, Anthropic/Claude, Bedrock

• Monitoring: Application Insights, Grafana, New Relic

• Experience establishing governance standards for data quality, privacy, ethics, and AI lifecycle management.

• Strong grasp of CI/CD practices, DevOps tooling, and engineering productivity metrics.

• Familiarity with Agile delivery processes and compliance frameworks such as SOC, PCI, or GDPR.

• Bachelor’s degree in a technical field; an advanced degree is a plus.

• Excellent communication, leadership, and cross-functional collaboration skills.

What You’ll Bring

A blend of technical depth and strategic insight, the ability to inspire engineering teams, and a passion for building systems that turn raw data and AI capabilities into business-defining outcomes. You balance innovation with reliability, thrive in complex environments, and elevate everyone around you.




## Full Description
About Us

Diligent is the AI leader in governance, risk and compliance (GRC) SaaS solutions, helping more than 1 million users and 700,000 board members to clarify risk and elevate governance. The Diligent One Platform gives practitioners, the C-Suite and the board a consolidated view of their entire GRC practice so they can more effectively manage risk, build greater resilience and make better decisions, faster.

At Diligent, we're building the future with people who think boldly and move fast. Whether you're designing systems that leverage large language models or part of a team reimaging workflows with AI, you'll help us unlock entirely new ways of working and thinking. Curiosity is in our DNA, we look for individuals willing to ask the big questions and experiment fearlessly - those who embrace change not as a challenge, but as an opportunity. The future belongs to those who keep learning, and we are building it together. At Diligent, you're not just building the future - you're an agent of positive change, joining a global community on a mission to make an impact.

Learn more at diligent.com or follow us on LinkedIn and Facebook

The Team:

Our Business Applications and Analytics team plays a pivotal role in driving business success through data-driven decision-making and operational excellence. This dynamic team manages enterprise-wide applications, including ERP, CRM, and BI systems. By harnessing the power of data and advanced analytical tools, we provide valuable insights that inform strategic initiatives, optimize processes, and enhance overall performance.

Position Overview:

Diligent is 'All-In' on AI and is seeking a dynamic and strategic AI leader to join our team as an AI Solutions Architect. As part of the Business Applications and Analytics team, this crucial role is designed to accelerate our Internal AI capabilities across multiple business functions, including Marketing, GTM/Sales, Customer Success & Support, Finance, HR, Legal, and Product and Engineering teams.

The primary goal of this position is to identify, prototype, deploy, and scale AI technologies and solutions that drive greater operational efficiency and effectiveness. The ideal candidate will be a technically adept individual with business acumen, able to bridge the gap between robust technical implementations and business needs, with the ability to partner with various business leaders to spot and act on opportunities for AI-driven transformation and innovation.

Key Responsibilities:

• Partner with business leaders to understand challenges, identify AI opportunities, and implement effective AI/GenAI solutions.

• Lead the ideation, prototyping, deployment, and scaling of AI/GenAI technologies and agentic solutions tailored to business needs.

• Develop and communicate strategic frameworks and roadmaps for AI initiatives aligned with business goals.

• Champion best practices in AI/ML and GenAI development—including responsible AI, privacy, security, and ethical guidelines.

• Collaborate with cross-functional teams to integrate AI tools within core business processes, ensuring seamless, high-value adoption.

• Stay abreast of AI best practices, tools, and methodologies and introduce them to the organization.

• Drive AI and Data literacy across the company through training, workshops, and continuous education initiatives.

• Ensure compliance with data protection and privacy regulations in all AI implementations.

• Monitor and evaluate the performance and effectiveness of AI solutions and continually refine them.

• Collaborate with stakeholders to define and achieve key performance indicators (KPIs) and return on investment (ROI) for AI projects.

• Advocate and implement AI ethical guidelines and best practices.

Required Qualifications:

• Solid Foundations: Bachelor's degree in Computer Science, AI/ML, Data Science, or a related technical field.

• Practical Tinkerer: 5+ years in a technical role (software, data, DevOps, etc.), with hands on experience building end-to-end prototypes using GenAI tools (GPTs, Hugging Face, open-source LLMs, LangChain, Scikit-learn, etc.).

• Curious Explorer: Demonstrates a hands-on approach to learning in prompt-engineering, fine-tuning, RAG pipelines, or API Integrations, with a commitment to rapid failure, iteration, and sharing findings.

• Data Wrangler: Possesses the ability to source, clean, and transform raw data, including spreadsheets, logs, APIs, or CRM exports, into structured inputs for AI experiments and prototypes.

• Code Crafter: Capable of writing scripts or small applications to connect models, cloud services, or data sources. Prior experience with TensorFlow, PyTorch, Azure, AWS, or GCP is beneficial, but willingness to learn is equally important.

• Business Translator: Experienced as a technical sales engineer or solutions consultant, capable of turning AI experiments into compelling stories and metrics that resonate with non-technical stakeholders.

• Responsible AI Mindset: Demonstrated experience in addressing privacy, security, bias, and ethics in professional work, with a strong familiarity with industry-specific data privacy, AI ethics, and compliance requirements.

• Team Player: Essential qualities include clear communication and a growth mindset, as you will collaborate with marketers, sales professionals, engineers and leaders.

Preferred Qualifications:

• Demonstrates strong knowledge of AI use cases, including NLP, computer vision, data analytics, predictive modelling, and translating technical capabilities into business value, along with proficiency in large language models (LLMs), prompt engineering, RAG architectures, MLOps, LLMOps, and GenAI application deployment.

• Advanced programming and data engineering skills, with Python preferred, and experience in cloud-based AI solutions (AWS, GCP, Azure).

• Ability to architect and deploy enterprise-scale AI solutions, collaborating across sales, product, and implementation teams to ensure adoption and measurable ROI.

• Strategic thinker with strong analytical and problem-solving skills, capable of driving measurable business outcomes through AI/GenAI.

What Diligent Offers You

• Creativity is ingrained in our culture. We are innovative collaborators by nature. We thrive in exploring how things can be differently both in our internal processes and to help our clients

• We care about our people. Diligent offers a flexible work environment, global days of service, comprehensive health benefits, meeting free days, generous time off policy and wellness programs to name a few

• We have teams all over the world. We may be headquartered in New York City, but we have office hubs in Washington D.C., Vancouver, London, Galway, Budapest, Munich, Bengaluru, Singapore, and Sydney.

• Diversity is important to us. Growing, maintaining and promoting a diverse team is a top priority for us. We foster and encourage diversity through our Employee Resource Groups and provide access to resources and education to support the education of our team, facilitate dialogue, and foster understanding.

Diligent created the modern governance movement. Our world-changing idea is to empower leaders with the technology, insights and connections they need to drive greater impact and accountability – to lead with purpose. Our employees are passionate, smart, and creative people who not only want to help build the software company of the future, but who want to make the world a more sustainable, equitable and better place.

Headquartered in New York, Diligent has offices in Washington D.C., London, Galway, Budapest, Vancouver, Bengaluru, Munich, Singapore and Sydney. To foster strong collaboration and connection, this role will follow a hybrid work model. If you are within a commuting distance to one of our Diligent office locations, you will be expected to work onsite at least 50% of the time. We believe that in-person engagement helps drive innovation, teamwork, and a strong sense of community.

We are a drug free workplace. Diligent is proud to be an equal opportunity employer. We do not discriminate based on race, color, religious creed, sex, national origin, ancestry, citizenship status, pregnancy, childbirth, physical disability, mental disability, age, military status, protected veteran status, marital status, registered domestic partner or civil union status, gender (including sex stereotyping and gender identity or expression), medical condition (including, but not limited to, cancer related or HIV/AIDS related), genetic information, or sexual orientation in accordance with applicable federal, state and local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Diligent's EEO Policy and Know Your Rights. We are committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at recruitment@diligent.com.

To all recruitment agencies: Diligent does not accept unsolicited agency resumes. Please do not forward resumes to our jobs alias, Diligent employees or any other organization location. Diligent is not responsible for any fees related to unsolicited resumes.



## Qualifications
* Proven experience building or deploying machine learning systems in production environments (not just academic or lab prototypes)
* Background in a top technology company, Tier 1 VC backed startup, advanced research institute, or high-caliber engineering team
* Solid understanding of ML fundamentals, including model development, optimization, and evaluation
* Hands-on experience with at least one major area of specialization:
* LLMs & Generative AI
* Computer Vision
* NLP / NLU
* Time Series & Forecasting
* Applied Deep Learning
* Familiarity with modern ML engineering workflows:
* Vector databases & embeddings
* Retrieval-augmented pipelines
* Experience with distributed systems, data infrastructure, or high-performance computing is a strong advantage
* Professionals with experience in AI Safety, alignment, privacy-preserving ML, or security-focused ML are also welcome
* Experience mentoring engineers, leading technical initiatives, or driving cross-functional collaboration is valued
* Candidates with a track record of publications, open-source contributions, patents, or shipped products demonstrating real-world impact will stand out
## Benefits
* We prioritize your confidentiality and privacy throughout the recruitment process
## Responsibilities
* Reinforcement Learning
* Recommendation Systems
* MLOps pipelines
* Model monitoring & observability
* Deployment to cloud or edge environments
* Insight on compensation structures across geographies, including equity-heavy offers, research-focused roles, or hybrid IC/lead tracks

## Full Description
About Us

Catalyst Labs is a leading talent agency with a specialized vertical in Applied AI, Machine Learning, and Data Science. We stand out as an agency that's deeply embedded in our clients recruitment operations.

We collaborate directly with Founders, CTOs, and Heads of AI at Tier 1 VC backed startups, scale ups and enterprise tech like Palatir, who are driving the next wave of applied intelligence from model optimization to productized AI workflows. We take pride in facilitating conversations that align with your technical expertise, creative problem-solving mindset, and long-term growth trajectory in the evolving world of intelligent systems.

This is a general / expression of interest, therefore by submitting your CV, you will be considered for upcoming roles with our clients.

Locations

Most of our client base is concentrated in California, New York and a few scattered across other States and Europe.

Who Can Apply

We are looking for professionals with demonstrated experience in AI, ML, and Data Science roles within reputed tech companies and/or from top 100 universities in the world. Visa sponsorship is available for existing H1b transfers. Student visas will only be considered on the academic pedigree - top 50 global universities.

Experience

From early-career engineers to senior ICs, leads and principals.

General Requirements by Role

• Proven experience building or deploying machine learning systems in production environments (not just academic or lab prototypes).

• Background in a top technology company, Tier 1 VC backed startup, advanced research institute, or high-caliber engineering team.

• Solid understanding of ML fundamentals, including model development, optimization, and evaluation.

• Hands-on experience with at least one major area of specialization:

• LLMs & Generative AI

• Computer Vision

• NLP / NLU

• Reinforcement Learning

• Recommendation Systems

• Time Series & Forecasting

• Applied Deep Learning

• Familiarity with modern ML engineering workflows:

• MLOps pipelines

• Model monitoring & observability

• Deployment to cloud or edge environments

• Vector databases & embeddings

• Retrieval-augmented pipelines

• Experience with distributed systems, data infrastructure, or high-performance computing is a strong advantage.

• Professionals with experience in AI Safety, alignment, privacy-preserving ML, or security-focused ML are also welcome.

• Strong coding proficiency (Python preferred) and familiarity with relevant frameworks such as PyTorch, TensorFlow, JAX, LangChain, Ray, etc.

• Experience mentoring engineers, leading technical initiatives, or driving cross-functional collaboration is valued.

• Candidates with a track record of publications, open-source contributions, patents, or shipped products demonstrating real-world impact will stand out.

Why Work With Us?

• Take advantage of the strong relationships we have built with Founders and CTOs.

• Work with recruiters who understand the difference between a fine-tuned model and a foundation model and wont ask if you know Python.

• We prioritize your confidentiality and privacy throughout the recruitment process.

• No Spamming.

• Support refining your resume or portfolio specifically for the roles we shortlist you for.

• Direct communication channels. Bypass gatekeepers and speak directly with the actual hiring manager and decision-makers.

• Insight on compensation structures across geographies, including equity-heavy offers, research-focused roles, or hybrid IC/lead tracks.




## Full Description
FutureSight is seeking an experienced and visionary Founding CEO to lead the launch of a new AI-native platform that transforms how government contractors win proposals.

Government contractors are drowning in complexity. Proposal teams juggle chasing SMEs, hunting through outdated content, and manually tracking compliance — coordinating across BD, legal, and finance. The result: slower proposals,lower win rates (<45%), and high stress.

Our venture reimagines this workflow. We’re building an AI-enabled orchestration platform that streamlines SME coordination, automates compliance tracking, and intelligently reuses knowledge — all while preserving the human + SME voice in proposals. Contractors move faster, reduce risk, and increase win rates.

Own the vision for a GovCon AI platform that streamlines people, content, and compliance across a $774B+ federal contracting market.

As Founding CEO, you will

• Win customers — Run pilots, shape pricing, and validate retention + expansion.

• Build the product — Work with FutureSight’s product/engineering pod to launch V1.

• Raise capital — Lead the seed round with our initial investment.

• Build your team — Hire your founding team and set the cultural foundation.

About FutureSight

FutureSight is a venture studio that co-creates and invests in B2B SaaS and Vertical AI startups alongside exceptional entrepreneurs. We give founders an unfair advantage — pairing hands-on studio support with early capital, thereby reducing risk and increasing the odds of success by 10x.

We’re led by a cross-functional team of builders and investors. Kevin Nguyen and Alan Smith lead venture design and product strategy. Prathna Ramesh applies her experience as a venture investor with capital strategy in every new business. Dennis Ensing mentors our ventures with operational and strategic expertise, Krista LaRiviere brings years of entrepreneurial and marketing experience as a multi-time exited founder, and Anupama Joshi drives founder excellence. John Carbrey (San Francisco), a successful software entrepreneur and people leader, adds deep insight into scaling startups from 0 to 1, having built and exited multiple prior SaaS ventures.

What We Bring

• Validated problem — You will enter a venture with a proven market need and strong momentum toward building and scaling.

• Studio bench strength — Designers, engineers, growth marketers, and fundraising pros are embedded from Day 1.

• Capital commitment — Initial pre-seed funding for early hires and building the MVP with potential for follow-on funding, and access to our investor and advisor network.

What You Bring

• Founder-level drive — You’re motivated to co-found a new venture as the CEO. With or without us, this is your calling.

• Startup scrappiness — You know what you’re signing up for. You’re familiar with the scrappiness of owning something from start to finish.

• Previous founding experience — You have co-founded a product company or B2B SaaS venture, or have been at a venture-backed company.

• Risk appetite and capacity — Read more on our post on the Entrepreneurial Risk Profile.

• GTM chops — Proven success in B2B SaaS sales, marketing, and customer engagement.

• Fundraising fluency — Able to craft investor narratives and close capital; well-networked in fintech and early-stage communities.

• People leadership — Magnet for top talent; coach and culture carrier.

• Industry experience — Background in government contracting, proposal management, or B2B SaaS for professional services.

What You Can Expect

• Daily active engagement with our team to: launch initial product, achieve initial market traction and prepare for seed fundraise.

• Full P/L ownership of the new entity.

• A significant equity stake in the business.

• This is a full-time role; we are seeking someone to dedicate themselves full-time and exclusively to building and owning a new SaaS venture.

Ready to build?

If this is the perfect opportunity for you, we want to hear from you!

Submit your Resume and LinkedIn profile and tell us more about why you think we should chat!

FutureSight is committed to diversity, equity, and inclusion. We welcome applicants of all backgrounds and experiences.



## Qualifications
* Experience working directly with LLMs, generative AI systems, or NLP models
* Familiarity with evaluations specific to AI safety, hallucination detection, or model alignment
* Experience designing annotation tasks or working with human labelers
* Understanding of mixed-method analysis (qualitative + quantitative)
* Experience building internal tools, scripts, or dashboards for evaluation workflows
* Familiarity with prompt engineering, RAG systems, or model fine-tuning
* Experience evaluating LLMs, multimodal models, or other generative AI systems at scale
* Expertise in designing annotation guidelines and managing large annotation teams or vendors
* Background in human factors, social science, or qualitative assessment methodologies
* Bachelor’s or Master’s degree in Data Science, Computer Science, Linguistics, Cognitive Science, HCI, Psychology, or a related field
* Experience: 5+ years in data science, machine learning evaluation, ML ops, annotation quality, safety evaluation, or a similar applied role
* Proficiency in Python for data analysis (pandas, NumPy, Jupyter, etc.)
* Experience working with large datasets, annotation tools, or model-evaluation pipelines
* Ability to design taxonomies, categorization schemes, or structured rating frameworks
* Analytical Strength: Ability to interpret unstructured data (text, transcripts, user sessions) and derive meaningful insights
* Communication: Strong ability to stitch together qualitative and quantitative findings into actionable guidance
## Responsibilities
* In this role, you'll represent the user perspective on new features, review and analyze data, and evaluate AI models powering everything from search and recommendations to other innovative features
* Collaborate with Data Scientists, Researchers, and Engineers to drive improvements across our platforms
* In this role, you will analyze AI outputs, develop evaluation frameworks, design qualitative, and translate findings into actionable improvements for product and engineering teams
* This role blends deep technical expertise with strong analytical judgment to assess, interpret, and improve the behavior of advanced AI models
* You will work cross-functionally with the Engineering and Project Managers, Product, and Research teams to ensure that AI experience is reliable, safe, and aligned with human expectations.","responsibilities":"AI Evaluation & Data Analysis
* Lead complex evaluations of model behavior, identifying issues in reasoning, factuality, interaction quality, safety, fairness, and user alignment
* Build evaluation datasets, annotation schemas, and guidelines for qualitative assessments
* Develop qualitative + semi-quantitative scoring rubrics for measuring human-perceived quality (e.g., helpfulness, factuality, clarity, trustworthiness)
* Run structured evaluations of model iterations and summarize strengths/weaknesses based on qualitative evidence
* Data Science & Modeling
* Collaborate with model developers to refine model behavior using findings from qualitative outputs
* Use statistical and computational methods to identify patterns in qualitative data (e.g., assigning loss patterns, error taxonomies, thematic categorization)
* Build dashboards, scripts, or workflows that codify evaluation metrics and automate portions of qualitative assessments
* Integrate qualitative evaluations with quantitative metrics (e.g., Precision@k, MRR, perplexity, accuracy, performance KPIs)
* Framework & Pipeline Development
* Create scalable pipelines for reviewing, annotating, and analyzing model outputs
* Define evaluation frameworks that capture nuanced human factors (e.g., uncertainty, trust calibration, conversational quality, interpretability)
* Develop processes to track feature quality and model performance over time and flag regressions
* Cross-Functional Collaboration
* Communicate evaluation results clearly to data scientists, engineers, and PMs
* Translate qualitative findings into clear loss patterns and actionable insights
* Work with product teams to ensure AI behaviors align with real-world user expectations

## Full Description
Imagine what you could do here. At Apple, great new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish!

Are you passionate about music, movies, and the world of Artificial Intelligence and Machine Learning? So are we! Join our Human-Centered AI team for Apple Products. In this role, you'll represent the user perspective on new features, review and analyze data, and evaluate AI models powering everything from search and recommendations to other innovative features. Collaborate with Data Scientists, Researchers, and Engineers to drive improvements across our platforms.

Description

We are looking for a Evaluation & Insights Engineer Human-Centered AI team to help evaluate and improve AI systems by combining data science, model behavior analysis, and qualitative insights. In this role, you will analyze AI outputs, develop evaluation frameworks, design qualitative, and translate findings into actionable improvements for product and engineering teams. This role blends deep technical expertise with strong analytical judgment to assess, interpret, and improve the behavior of advanced AI models. You will work cross-functionally with the Engineering and Project Managers, Product, and Research teams to ensure that AI experience is reliable, safe, and aligned with human expectations.","responsibilities":"AI Evaluation & Data Analysis

Lead complex evaluations of model behavior, identifying issues in reasoning, factuality, interaction quality, safety, fairness, and user alignment.

Build evaluation datasets, annotation schemas, and guidelines for qualitative assessments.

Develop qualitative + semi-quantitative scoring rubrics for measuring human-perceived quality (e.g., helpfulness, factuality, clarity, trustworthiness).

Run structured evaluations of model iterations and summarize strengths/weaknesses based on qualitative evidence.

Data Science & Modeling

Collaborate with model developers to refine model behavior using findings from qualitative outputs.

Use statistical and computational methods to identify patterns in qualitative data (e.g., assigning loss patterns, error taxonomies, thematic categorization).

Build dashboards, scripts, or workflows that codify evaluation metrics and automate portions of qualitative assessments.

Integrate qualitative evaluations with quantitative metrics (e.g., Precision@k, MRR, perplexity, accuracy, performance KPIs).

Framework & Pipeline Development

Create scalable pipelines for reviewing, annotating, and analyzing model outputs.

Define evaluation frameworks that capture nuanced human factors (e.g., uncertainty, trust calibration, conversational quality, interpretability).

Develop processes to track feature quality and model performance over time and flag regressions.

Cross-Functional Collaboration

Communicate evaluation results clearly to data scientists, engineers, and PMs.

Translate qualitative findings into clear loss patterns and actionable insights

Work with product teams to ensure AI behaviors align with real-world user expectations.

Preferred Qualifications

Experience working directly with LLMs, generative AI systems, or NLP models.

Familiarity with evaluations specific to AI safety, hallucination detection, or model alignment.

Experience designing annotation tasks or working with human labelers.

Understanding of mixed-method analysis (qualitative + quantitative).

Experience building internal tools, scripts, or dashboards for evaluation workflows.

Familiarity with prompt engineering, RAG systems, or model fine-tuning.

Experience evaluating LLMs, multimodal models, or other generative AI systems at scale.

Expertise in designing annotation guidelines and managing large annotation teams or vendors.

Background in human factors, social science, or qualitative assessment methodologies.

Minimum Qualifications

Bachelor’s or Master’s degree in Data Science, Computer Science, Linguistics, Cognitive Science, HCI, Psychology, or a related field.

Experience: 5+ years in data science, machine learning evaluation, ML ops, annotation quality, safety evaluation, or a similar applied role.

Technical Skills:

Proficiency in Python for data analysis (pandas, NumPy, Jupyter, etc.).

Experience working with large datasets, annotation tools, or model-evaluation pipelines.

Ability to design taxonomies, categorization schemes, or structured rating frameworks.

Analytical Strength: Ability to interpret unstructured data (text, transcripts, user sessions) and derive meaningful insights.

Communication: Strong ability to stitch together qualitative and quantitative findings into actionable guidance.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .




## Full Description
Description :

CYSSC is seeking a consultant role to lead the development of short-term and long-term AI acceleration strategies for the division. This role will focus on creating a comprehensive roadmap for AI adoption establishing governance frameworks and designing scalable technology architectures that align with organizational priorities. The consultant will work closely with senior leadership and cross-functional teams to identify high-value use cases define prioritization criteria and ensure responsible AI practices.

The ideal candidate will bring deep expertise in enterprise architecture AI strategy and data governance combined with strong communication skills to deliver executive-level presentations and actionable plans.

Responsibilities :

• Develop and deliver a comprehensive AI acceleration strategy including short-term and long-term roadmaps.

• Define KPIs and ROI models to measure business impact and technical success of AI initiatives.

• Establish governance frameworks for AI adoption including data strategy compliance and responsible AI principles.

• Assess business value and technical feasibility of AI use cases to guide prioritization.

• Design scalable technical architectures for AI platforms data pipelines and integration patterns.

• Recommend cloud-based AI solutions and establish MLOps practices for model lifecycle management.

• Collaborate with stakeholders to align technical solutions with business objectives and ensure successful delivery.

• Apply enterprise architecture frameworks (TOGAF Zachman or similar) to align AI initiatives with organizational standards.

• Prepare executive-level presentations and documentation for leadership reviews.

• Provide guidance on vendor selection partnership strategies and emerging AI technologies.

Requirements

Experience and Skill Set Requirements :

Must Haves :

• Experience in developing and executing AI adoption strategies for short-term and long-term horizons.

• Experience in defining and implementing KPI and ROI frameworks to measure business impact and technical success.

• Experience in designing governance models for AI initiatives including data strategy compliance and responsible AI principles.

• Experience in assessing business value and technical feasibility of AI use cases to guide prioritization.

• Experience in designing scalable technical architectures for AI platforms data pipelines and integration patterns.

• Experience in recommending and guiding implementation of cloud-based AI solutions and MLOps practices.

Skill Set Requirements :

AI Strategy & Governance :

• Experience in developing and executing AI adoption strategies for short-term and long-term horizons.

• Experience in defining and implementing KPI and ROI frameworks to measure business impact and technical success.

• Experience in designing governance models for AI initiatives including data strategy compliance and responsible AI principles.

• Experience in assessing business value and technical feasibility of AI use cases to guide prioritization.

• Ability to guide cultural and operational shifts required for AI adoption including stakeholder alignment and readiness assessments.

• Experience in identifying risks (bias privacy compliance) and implementing mitigation strategies beyond just governance frameworks.

• Experience in ensuring adherence to ethical AI standards and regulatory requirements.

• Ability to evaluate and recommend external AI vendors platforms and academic partnerships for accelerating delivery.

• Strong ability to translate complex AI concepts into clear actionable insights for senior leadership and non-technical stakeholders.

• Knowledge of emerging AI trends and ability to assess their relevance for future strategy.

AI Implementation :

• Experience in designing scalable technical architectures for AI platforms data pipelines and integration patterns.

• Experience in recommending and guiding implementation of cloud-based AI solutions and MLOps practices.

• Experience in collaborating with stakeholders to align technical solutions with business objectives and ensure successful delivery.

Enterprise Architecture :

• Experience in applying enterprise architecture frameworks (TOGAF Zachman or similar) to align AI initiatives with organizational standards.

Required Skills :

Experience and Skill Set Requirements : Must Haves : Experience in developing and executing AI adoption strategies for short-term and long-term horizons. Experience in defining and implementing KPI and ROI frameworks to measure business impact and technical success. Experience in designing governance models for AI initiatives including data strategy compliance and responsible AI principles. Experience in assessing business value and technical feasibility of AI use cases to guide prioritization. Experience in designing scalable technical architectures for AI platforms data pipelines and integration patterns. Experience in recommending and guiding implementation of cloud-based AI solutions and MLOps practices. Skill Set Requirements : AI Strategy & Governance : Experience in developing and executing AI adoption strategies for short-term and long-term horizons. Experience in defining and implementing KPI and ROI frameworks to measure business impact and technical success. Experience in designing governance models for AI initiatives including data strategy compliance and responsible AI principles. Experience in assessing business value and technical feasibility of AI use cases to guide prioritization. Ability to guide cultural and operational shifts required for AI adoption including stakeholder alignment and readiness assessments. Experience in identifying risks (bias privacy compliance) and implementing mitigation strategies beyond just governance frameworks. Experience in ensuring adherence to ethical AI standards and regulatory requirements. Ability to evaluate and recommend external AI vendors platforms and academic partnerships for accelerating delivery. Strong ability to translate complex AI concepts into clear actionable insights for senior leadership and non-technical stakeholders. Knowledge of emerging AI trends and ability to assess their relevance for future strategy. AI Implementation : Experience in designing scalable technical architectures for AI platforms data pipelines and integration patterns. Experience in recommending and guiding implementation of cloud-based AI solutions and MLOps practices. Experience in collaborating with stakeholders to align technical solutions with business objectives and ensure successful delivery. Enterprise Architecture : Experience in applying enterprise architecture frameworks (TOGAF Zachman or similar) to align AI initiatives with organizational standards.

Key Skills

IT Experience,Apache Hive,APIs,Spring,.NET,Solution Architecture,J2EE,Java,Microservices,Azure,Project Implementation,Oracle

Employment Type : Full Time

Experience : years

Vacancy : 1




## Full Description
Are you a systems thinker who sees the whole picture business vision, technical strategy, and the orchestration required to bring it all together? Do you thrive in environments where innovation is rapid, ambiguity is normal, and the work sits at the intersection of AI, product, and human experience?

Our client is building a next-generation fashion-tech platform that goes beyond the limitations oftoday's virtual try-on solutions.

They are looking for a Solution Architect who can translate this vision into a cohesive, scalable, and high-performing architecture.

The Solution Architect is the strategic bridge between business vision and technical execution. This role is not about coding-it's about orchestration, systems thinking, and architectural clarity.

You will work closely with the CEO, CPO/CDO, Product teams, ML engineers, and fashion technologists to design the blueprint, align cross-functional teams, and ensure every component of this platform integrates seamlessly.

Key Responsibilities

• Translating Business Goals Into Technical Requirements

• Cross-Functional Orchestration & Harmonization

Requirements

• Proven experience in technology with progression from engineering to architecture or technical leadership.

• Strong understanding of system architecture fundamentals: design patterns, trade-offs, scaling principles.

• Conceptual understanding of AI/ML workflows: training, inference, model behaviour, data quality metrics.

• Good grasp of data architecture basics-pipelines, ETL/ELT, schemas, data modelling.

• Strong communication skills and ability to extract clarity from vague or evolving requirements.

• Ability to create visual documentation such as architecture diagrams, user flows, and wireframes.

Nice-to-Have

• Familiarity with AI Agents, automated workflows, and agentic AI.

• Fashion or beauty industry exposure.

• Experience with ROI-driven decision-making and business outcome metrics.

• Experience with ML tools like TensorFlow, PyTorch, or cloud-based ML platforms.

Apply now and help create the future of intelligent personalization.

Seniority level

• Associate

Employment type

• Full-time

Job function

• Information Technology and Design

Industries

• Technology, Information and Media, IT System Design Services, and Retail Apparel and Fashion



Senior Researcher - Safety Systems, Misalignment Research