The AI Engineering team is responsible for working closely with the research and modeling teams to create state-of-the-art NLP models for specific tasks, and deploy them in a production setting designed to serve our customers at scale. We are looking for a Machine Learning Engineer to help build and evaluate the core intelligence behind our agentic AI systems. This role will play a key part in designing and owning evaluation frameworks that ensure quality, safety, and performance across complex agentic systems.
This a hybrid role with 10-12 days of in-office presence per month to balance flexibility with collaboration.
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
$170,000 - $190,000 a year
Compensation package also includes a performance bonus on top of the listed salary range
Separately, we also offer a compelling equity grant comprised of stock options
Benefits include:
Competitive compensation with stock options
Comprehensive medical, vision, and dental insurance
401k matching
Fitness and wellness stipend
Mental well-being benefits
Professional learning and development stipend
Parental leave, including adoptive and foster parents
3 weeks paid time off (increases with tenure) along with sick leave, bereavement and jury duty
