Applied AI/ML Lead

What you'll do

• Design, train, evaluate, and fine-tune machine learning, deep learning, and large language models for business use cases.
• Build and maintain scalable ML, feature, and data pipelines for production deployment and monitoring.
• Perform feature engineering, data validation, and preprocessing on large, complex datasets to ensure model quality.
• Prototype and evaluate new AI techniques including generative AI, RAG, and agentic frameworks.
• Integrate AI services into applications via APIs while optimizing for performance, latency, and cost.
• Implement testing frameworks to detect model drift, bias, and degradation while adhering to responsible AI standards.
• Lead projects from initial requirement gathering through design, implementation, and final delivery.
• Provide technical documentation and code review support to junior engineers.

What we're looking for

• Master's degree in a quantitative field or equivalent practical experience.
• 6+ years of hands-on experience building and deploying ML/AI models in production settings.
• Proficiency in Python, SQL, Relational Databases, Linux, and frameworks like PyTorch or scikit-learn.
• Solid understanding of ML fundamentals, including deep learning, generative AI, LLMs, and RAG.
• Proficiency in MLOps tooling including Docker, Kubernetes, CI/CD, and pipeline tools like MLflow or Airflow.
• Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) and its ML services.
• Familiarity with software engineering best practices including Git, testing, code review, and API design.
• Experience with vector databases, agentic AI frameworks, or responsible AI in regulated industries (preferred).