Lead ML/AI Platform Engineer

📋 Description

• Own the ML/AI platform: lead training infra, model serving, inference pipelines, registries
• Set technical direction: define ML/AI architecture, tooling standards, and build-versus-buy
• Build production ML systems: oversee feature engineering, training, deployment, monitoring, and
• Drive GenAI and LLM engineering: strategies for RAG, prompt engineering, evaluation, fine-tuning
• Develop agentic capabilities: evaluate emerging agent tech with guardrails for regulated
• Own the serving layer: design scalable ML services and API contracts for Java microservices

🎯 Requirements

• Senior engineering experience: 8+ years in software or ML, 5+ years shipping production ML systems.
• Technical leadership: shaping ML strategy and mentoring engineers.
• AWS ML expertise: SageMaker, Bedrock, AgentCore for GenAI/agent apps.
• Open-source ML tooling: JupyterLab, Spark, MLflow, etc.
• AWS platform knowledge: S3, Athena, Redshift, Glue, Step Functions, Lambda; strong SQL.
• GenAI/LLM expertise: RAG, prompt engineering, evaluation; cost, latency, safety trade-offs.

🎁 Benefits

• Equity compensation package.
• Remote-friendly benefits: Flexible Time Off, healthcare coverage, disability insurance, learning