AI​/ML Engineer

Full Description

Position: AI / ML Engineer

Job Overview

Vision Tact is seeking a highly skilled AI / Machine Learning Engineer to join our core Data Science and AI department.

The selected candidate will play a pivotal role in developing, training, and deploying scalable AI systems that power our automation, computer vision, and predictive analytics solutions.

You will work alongside a multidisciplinary team of data scientists, automation engineers, GIS specialists, and business strategists to translate real‑world challenges into intelligent, data‑driven solutions.

From data exploration and feature engineering to model optimization and API deployment, this role offers the opportunity to work across the entire AI development lifecycle

—from research to production.

Key Responsibilities

• Design, train, and optimize machine learning and deep learning models for diverse applications, including computer vision, NLP, predictive analytics, and automation

.

• Collaborate with data scientists and software developers to build AI‑driven features into production‑grade systems.

• Develop and manage data pipelines for model training and inference using modern ETL tools and frameworks.

• Implement and maintain MLOps practices to automate model training, validation, and deployment workflows.

• Work with large, structured and unstructured datasets from multiple sources (databases, APIs, geospatial feeds).

• Develop RESTful APIs or microservices to integrate AI models into applications and automation systems.

• Evaluate model performance and tune hyperparameters for optimal accuracy, precision, and scalability.

• Collaborate with business teams to define problem statements, success metrics, and AI solution roadmaps.

• Document models, datasets, and experiments thoroughly for reproducibility and collaboration.

• Stay updated on the latest AI research, frameworks, and technologies to incorporate innovation into Vision Tact projects.

Required Skills & Tools

• Programming

Languages:

Python (primary), R (optional), and familiarity with JavaScript/Type Script for API integration.

• Frameworks & Libraries: Tensor Flow, PyTorch, Scikit‑learn, OpenCV, Transformers, Hugging Face.

• Data Handling: Pandas, Num Py, SQL/No

SQL databases, and data preprocessing for ML workflows.

• MLOps / Deployment: Docker, MLflow, FastAPI, Kubernetes, or AWS Sage Maker.

• Version Control: Git/Git Hub for collaborative development.

• Visualization Tools: Matplotlib, Seaborn, Plotly, or Dash.

• Optional Exposure: Lang Chain, LLM fine‑tuning, and vector database integrations (e.g., Pinecone, FAISS).

• Soft Skills: Analytical mindset, problem‑solving ability, and cross‑functional communication.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.

• Minimum 3 years of applied experience in AI or machine learning model development.

• Proven portfolio or Git Hub repository demonstrating ML/AI projects (required).

• Certifications such as Tensor Flow Developer

, AWS AI Engineer

, or Deep Learning Specialization are a plus.

• Prior experience in deploying models to production environments (API, microservice, or edge AI) preferred.

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