Machine Learning Engineer Lead

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products. This role combines deep ML expertise with distributed systems engineering and AI platform development.

In this role you will be a hands-on engineer and leader that will lead a high-performing team of 4-5 ML engineers, drive platform-level decisions, and ensure enterprise-grade scalability, reliability, and responsible AI compliance.

Responsibilities:

• Lead, mentor, and grow a team of 4-5 ML engineers.
• Provide architectural direction and code-level guidance.
• Establish engineering best practices for ML system design, testing, and deployment.
• Conduct design reviews, performance reviews, and technical roadmap planning.
• Architect distributed ML systems serving multiple global products.
• Standardize infrastructure patterns for LLM serving and retrieval systems.
• Define and implement enterprise-ready agentic frameworks.
• Architect multi-step reasoning systems.
• Lead decisions on deterministic workflows vs. autonomous agents.
• Implement guardrails, safety layers, and traceability mechanisms.
• Develop evaluation frameworks to measure reasoning quality, hallucination rates, and reliability.
• Establish CI/CD standards for ML lifecycle management.
• Ensure compliance with enterprise data governance and responsible AI standards.

Requirements

• 8-10 years of Machine Learning/Software Engineer experience
• 2-3 years of people management experience.
• Master’s degree or bachelor's degree, computer science degree is highly desirable.
• Strong software engineering background with experience in building system design, architecting AI feature/products that caters large number of users and deals with large volume of unstructured data
• Experience with ML deployment to production