Design, build, and optimize the pipelines and agent systems that drive live customer interactions
Build ranking, scoring, and routing models for live inference
Architect tool-calling flows, agent memory, and multi-turn reasoning
Optimize token usage, caching, and cost-performance tradeoffs
Build and maintain ML APIs and microservices using Docker and Kubernetes
Collaborate cross-functionally on platform-wide architecture and data contracts

Requirements

7+ years of experience in ML, AI, or data engineering roles
Expert-level Python for backend, ML workflows, and orchestration
Experience with modern LLM frameworks such as LangChain or LangGraph
Deep knowledge of vector databases and retrieval systems
Production experience with reinforcement learning
Comfort with distributed systems, Docker, and Kubernetes
Experience building and maintaining streaming or real-time pipelines
A track record of shipping complex systems that work in production

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Pythonmachine learningartificial intelligencedata engineeringLLM frameworksvector databasesreinforcement learningstreaming pipelinesreal-time pipelinesmicroservices

Soft Skills

collaborationcross-functional teamwork