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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.
Masters degree or bachelors 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
U.S. National Base Pay Range: $115,400 - $192,300. Geographic differentials may apply in some locations to better reflect local market rates.
This job is eligible for an annual incentive bonus.
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