Machine Learning Engineer Lead

Our client is a leading global provider of legal, regulatory and business information and analytics that help customers increase productivity, improve decision-making and outcomes, and advance the rule of law around the world.

They help lawyers win cases, manage their work more efficiently, serve their clients better and grow their practices. They assist corporations in better understanding their markets, monitoring their brands and competition, and in mitigating business risk. They collaborate with universities to educate students, and support nation-building with governments and courts by making laws accessible and strengthening legal infrastructures. They partner with leading global associations and customers to collect evidence against war criminals and provide tools to combat human trafficking.

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.