Architect and operate end-to-end production AI systems
Develop production-grade cloud-native environments optimized for AI/ML model training, serving, and orchestration
Help define how enterprise-grade AI systems are designed, deployed, and operated
Mentor junior engineers and drive engineering standards across projects
Build agentic systems with multi-step reasoning, orchestration, and tool/function calling
Develop evaluation harnesses, traces, and replay tooling for agent behavior
Integrate with vector stores, graph databases, Redis, DynamoDB, and ElastiCache to enable AI applications

7+ years of professional software engineering experience
Strong proficiency in Python
Experience building and operating production ML systems end-to-end
Hands-on experience with AWS and/or Databricks
Experience integrating GenAI and LLMs using advanced prompt engineering
Familiarity with MCP (Model Context Protocol)
Strong ML fundamentals, including algorithms, evaluation metrics, and model tuning
Bachelor's degree in information technology, computer science, or a related field
Experience with data handling, including data cleaning, feature engineering, and preprocessing
Ability to operate autonomously on complex technical initiatives
Experience with CI/CD and DevOps, including containerization and deployment pipelines.

Senior Machine Learning Engineer

Key skills