Lead Machine Learning Engineer

What you'll do

• Design, develop, and scale core agentic engines and multi-agent workflow solutions.
• Build and integrate scalable evaluation and observability frameworks to ensure model predictability.
• Deploy production AI solutions including consumer experiences, recommendation engines, and conversational assistants.
• Ensure all AI/ML applications adhere to data privacy standards and regulatory auditability.
• Apply LLM optimization, retrieval-augmented generation (RAG), and multi-agent design patterns to production systems.
• Provide technical direction, architectural oversight, and rigorous code reviews for engineering teams.

What we're looking for

• At least 6 years of experience designing and building data-intensive solutions using distributed computing.
• At least 4 years of experience programming with Python, Scala, or Java.
• Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field (preferred).
• 3+ years of experience with GenAI frameworks and Vector Databases (preferred).
• 3 years of experience building, scaling, and optimizing LLM or GenAI orchestration systems in production (preferred).
• 2+ years of experience building automated evaluations and observability pipelines for LLMs (preferred).
• 3+ years of on-the-job experience with an industry-recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow (preferred).