Machine Learning Engineer
Core
Design and manage federated AI ecosystems, including agents and enterprise AI solutions, while orchestrating agent deployment across distributed systems.
Role type
Senior IC machine learning engineer (AI infrastructure)
Builds
Production-grade AI/ML systems, reusable modules for LLM routing and inference optimization, and high-performance evaluation pipelines.
Domain
Enterprise AI infrastructure, distributed systems, and agentic AI
Deliverable
production ML models
Required skills
Python, PyTorch, Docker, Kubernetes, enterprise software architecture, agent orchestration, MLOps, classical machine learning
Preferred skills
Cloud platforms (AWS, Azure, GCP), infrastructure-as-code, LangGraph, LangChain, PydanticAI, vector databases, RAG architectures
Technologies
Python, PyTorch, Docker, Kubernetes, AWS, Azure, GCP, LangGraph, LangChain, PydanticAI
Responsibilities
Transform rapid prototypes into production-grade AI/ML systems; identify repeatable patterns and convert them into reusable modules; design and implement AI infrastructure for federated agent development; manage and orchestrate AI agents; build high-performance evaluation pipelines and observability frameworks; integrate AI-powered tools into existing workflows and CI/CD pipelines; teach AI infrastructure best practices across teams.
Seniority
Senior, hands-on IC
