Senior Machine Learning Engineer

What you'll do

• Build core agent infrastructure including the runtime, tool execution layer, and memory systems.
• Develop production-ready code for sub-second orchestration, cost-aware routing, and high-throughput inference.
• Design and manage ML workflows for model customization, serving, and lifecycle management at enterprise scale.
• Prototype and implement novel approaches to agent reasoning, tool orchestration, and evaluation.
• Manage the full production lifecycle including deployment, monitoring, observability, and incident response.
• Translate customer feedback and deployment performance into actionable platform roadmap improvements.

What we're looking for

• Ph.D. or M.S. in Computer Science or a related field is required.
• Candidates must have 5+ years of experience building and deploying production ML systems for real users at scale.
• Proficiency in Python and/or Java is required for designing APIs and microservices.
• Candidates must have deep hands-on experience with at least one modern deep learning framework such as PyTorch, TensorFlow, or JAX.
• Production experience with LLMs including prompt engineering, fine-tuning, or building LLM-powered applications is required.
• Experience with cloud platforms like AWS or Azure and data infrastructure like Postgres, Redis, or Snowflake is required.
• Experience with agent loops, RAG pipelines, or fine-tuning/serving infrastructure in production systems is preferred.
• Publications or open-source contributions are a plus (preferred).