Senior Machine Learning Engineer

What you'll do

• Architect and evolve a multi-tenant AI/ML platform that unifies traditional machine learning with Generative AI and LLM orchestration.
• Design and implement production-grade AI agents, advanced chatbots, and multi-agent systems with state management and memory architectures.
• Build high-throughput, low-latency application backends and orchestration layers to support internal business units.
• Act as a technical anchor for the Data Science team by enforcing engineering standards and leading design and security reviews.
• Evaluate and implement modern AI infrastructure tools, including vector databases, embedding pipelines, and serverless compute paradigms.
• Develop robust data pipelines and backend services to transform complex datasets into reliable products for go-to-market and product teams.
• Manage the end-to-end technical strategy for AI products from initial requirements through global deployment and optimization.

What we're looking for

• Must hold an M.S. or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Must have extensive experience as a Senior or Lead ML Engineer architecting and operating production-grade ML platforms and distributed backends.
• Requires 3+ years of dedicated ML Engineering experience within a large-scale enterprise environment handling petabyte-scale data.
• Must possess deep expertise in both traditional ML lifecycles and Generative AI patterns, including RAG pipelines and agentic systems.
• Must have mastery of Python and proficiency with modern backend ecosystems, including familiarity with React and TypeScript.
• Requires hands-on experience with LLM frameworks like LangGraph or LangChain and established LLMOps foundations for evaluation and guardrailing.
• Must have experience with Docker, Kubernetes, Terraform, and cloud platforms such as GCP, AWS, or Azure.
• Must be authorized to receive software or technology controlled under U.S. export control laws.