Senior AI/ML Engineer

• Architect, train, evaluate, and optimize machine learning models, owning the full model lifecycle from experimentation to production
• Design and build AI agents and automated workflows using Amazon Quick and AWS orchestration tools
• Define and implement efficient ML workflows, optimizing for performance, scalability, and cost
• Architect and maintain serverless data pipelines using AWS Glue, Step Functions, Lambda, and EventBridge Scheduler
• Lead the design of our analytics service engine for ingesting, transforming, and querying data across S3 storage (Excel/CSV files, Delta Tables, library files)
• Establish MLOps practices, CI/CD pipelines, and infrastructure standards for the team
• Integrate with external systems (e.g., SAP, Salesforce) and design robust data-sourcing strategies
• Design and build REST APIs and model-serving infrastructure for production workloads
• Mentor junior engineers, conduct code reviews, and set technical standards
• Partner with cross-functional stakeholders to translate business needs into ML solutions

Required Technical Skills

• Programming: Expert in Python with a track record of writing clean, well-tested, production-grade code
• ML Frameworks: Strong, hands-on experience with PyTorch, TensorFlow, and scikit-learn
• Model Development: Deep understanding of model training, evaluation, inference, and optimization for efficient ML at scale
• AI Agents & Automation: Proven experience building AI agents and automated workflows; proficient with Amazon Quick
• MCP & Tool Integration: Experience building and integrating Model Context Protocol (MCP) servers to connect LLMs and AI agents with external tools, data sources, and services
• APIs & Serving: Strong experience designing REST APIs and deploying/serving ML models in production
• Cloud & Infrastructure: Solid experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker)
  • MLOps & Tooling: Proficient with Git, CI/CD pipelines, and ML infrastructure best practices