Data Scientist + ML Engineer (Gen AI)

Qualifications

• This position requires a balance of technical depth and creative problem-solving
• You should be comfortable working with large, complex datasets and possess a strong grasp of modern ML frameworks, distributed computing environments, and end-to-end data pipelines
• Bachelor’s degree in Computer Science or related field from an accredited U.S. institution
• 2+ years of experience in Machine Learning or Software Engineering
• Expert-level proficiency in Python and familiarity with deep learning frameworks such as PyTorch
• Strong foundation in machine learning algorithms, data preprocessing, and evaluation techniques
• Demonstrated experience working with diffusion models, stable diffusion, or large language models (LLMs)
• Excellent analytical, problem-solving, and debugging skills
• Strong communication and documentation skills with the ability to explain complex concepts clearly
• Ability to work independently in a fast-paced, iterative development environment

Benefits

• Benefits: Medical, Dental, Vision, Life, Retirement
• Duration: 12 months contract with possible extension
• Rate: $70-$74.00/hr on w2 , DOE

Responsibilities

• In this role, you will be responsible for developing, fine-tuning, and applying advanced generative AI models — including diffusion models, large language models (LLMs), and other state-of-the-art architectures
• You will collaborate closely with cross-functional partners in research, data engineering, and operations to deliver high-quality machine learning solutions and scalable datasets
• Design and Implement LLM-Driven Synthetic Data Pipelines: Design and build work flows using LLMs and Gen AI techniques to create high-volume, high-quality synthetic data for model training and testing
• Design, implement, and deploy machine learning models with a focus on generative AI (diffusion models, LLMs, and related architectures)
• Fine-tune, evaluate, and optimize large language models for specific downstream tasks and data needs
• Develop and maintain scalable data pipelines supporting training, evaluation, and inference workflows
• Conduct exploratory data analysis to surface insights and identify opportunities for model or data improvement
• Partner cross-functionally with researchers, engineers, and data program managers to define requirements and deliver high-impact ML solutions
• Build and enhance internal tools, libraries, and automation work flows to accelerate experimentation and iteration

Full Description

Job Description

Data Scientist + ML Engineer (Gen AI)

Company: Pride Global

Location: Cupertino, CA (On-site, Remote)

Type: Contract

Benefits: Medical, Dental, Vision, Life, Retirement

Posted: 11 hours ago

Job Description

Data Scientist + ML Engineer (Gen AI)

Location: Cupertino, CA (Remote, but needs to be onsite occasionally)

Duration: 12 months contract with possible extension

Rate:$70-$74.00/hr on w2 , DOE

We are looking for a highly skilled Data Scientist + ML Engineer (Generative AI) to join our client's team.

In this role, you will be responsible for developing, fine-tuning, and applying advanced generative AI models — including diffusion models, large language models (LLMs), and other state-of-the-art architectures.

You will collaborate closely with cross-functional partners in research, data engineering, and operations to deliver high-quality machine learning solutions and scalable datasets.

This position requires a balance of technical depth and creative problem-solving.

You should be comfortable working with large, complex datasets and possess a strong grasp of modern ML frameworks, distributed computing environments, and end-to-end data pipelines.

Responsibilities

• Design and Implement LLM-Driven Synthetic Data Pipelines: Design and build work flows using LLMs and Gen AI techniques to create high-volume, high-quality synthetic data for model training and testing.

• Design, implement, and deploy machine learning models with a focus on generative AI (diffusion models, LLMs, and related architectures)

• Fine-tune, evaluate, and optimize large language models for specific downstream tasks and data needs

• Develop and maintain scalable data pipelines supporting training, evaluation, and inference workflows

• Conduct exploratory data analysis to surface insights and identify opportunities for model or data improvement

• Partner cross-functionally with researchers, engineers, and data program managers to define requirements and deliver high-impact ML solutions

• Build and enhance internal tools, libraries, and automation work flows to accelerate experimentation and iteration

Required Experience And Skills

• Bachelor’s degree in Computer Science or related field from an accredited U.S. institution

• 2+ years of experience in Machine Learning or Software Engineering

• Expert-level proficiency in Python and familiarity with deep learning frameworks such as PyTorch

• Strong foundation in machine learning algorithms, data preprocessing, and evaluation techniques

• Demonstrated experience working with diffusion models, stable diffusion, or large language models (LLMs)

• Excellent analytical, problem-solving, and debugging skills

• Strong communication and documentation skills with the ability to explain complex concepts clearly

• Ability to work independently in a fast-paced, iterative development environment