Lead Machine Learning Engineer

What you'll do

Design and development of ML evaluation systems for agentic and LLM-based architectures

Translate research ideas into production-grade ML systems with measurable impact

Partner closely with Research, Product, and Platform teams to productize experiments into robust AI solutions

Stay current with advancements in ML, NLP, and LLM systems, contributing actively to technical discussions across teams

Mentor and support other engineers through design reviews, feedback, and knowledge sharing.

What you'll need

Deep experience in NLP and modern ML systems, including hands-on experience with LLM-based or agentic systems.

Strong architectural skills, with proven experience designing complex software systems along with production experience with Python, AWS, Kubernetes, and/or Docker.

Experience implementing technical solutions, tackling tough engineering problems to help build our products and a deep passion for Machine Learning.

A Bachelor’s Degree in CS or other related fields

Desire to learn new things, work closely with peers from different teams, and open to teach and learn from others.

Demonstrate proficiency in the technical mentorship of junior and mid-level engineers, driving the adoption of best practices and ensuring architectural alignment for scalability and extensibility.

What we'd like to see

Experience building and evaluating agentic systems at scale.

Production experience with LLM-centric services (e.g., inference, orchestration, evaluation, monitoring)

Familiarity with large-scale ML experimentation, benchmarking, or simulation framework

Knowledge of techniques for optimizing model architectures for faster inference

Experience with AWS, CI/CD, Kafka, Athena