Lead ML/AI Platform Engineer

📋 Description

• Own the ML/AI platform: lead the architecture and operation of training infrastructure, model
• Set technical direction: define ML/AI architecture, tooling standards, build-versus-buy decisions.
• Build production ML systems: oversee feature engineering, model training, tuning, registration
• Drive GenAI and LLM engineering: strategies for RAG, prompt engineering, evaluation, fine-tuning
• Develop agentic capabilities: evaluate emerging agent technologies and workflows, with appropriate
• Own the serving layer: design scalable ML services and API contracts that integrate with Java

🎯 Requirements

• Senior engineering experience: 8+ years in software or ML, with 5+ years delivering production ML
• Technical leadership: experience shaping ML strategy, mentoring engineers, and guiding architecture
• AWS ML expertise: hands-on with SageMaker for training/tuning/endpoints, Bedrock and AgentCore for
• Open-source ML tooling: JupyterLab, Spark, MLflow, etc.
• AWS platform knowledge: strong SQL and services like S3, Athena, Redshift, Glue, Step Functions
• GenAI/LLM expertise: production experience with RAG, prompts, evaluation, cost/latency/safety

🎁 Benefits

• Equity compensation package
• Flexible Time Off (FTO)
• Medical, dental, and vision coverage with premiums covered where applicable
• Disability and life insurance
• Learning and career development opportunities
• Remote-work setup reimbursement