We are seeking a Senior MLOps Engineer to own the end-to-end ML lifecycle – from model packaging and deployment to monitoring, observability, optimization and scaling – for a custom-built inference platform powering a live conversational shopping agent.
Requirements
- Bachelor's or Master's degree in Computer Science, Data Science, or a related field, or equivalent experience
- 5-8+ years of experience in Software Engineering, ML Engineering, Platform Engineering, or Infrastructure Engineering with direct ownership of production ML serving systems
- Hands-on experience deploying and maintaining LLMs and deep learning models, in production environments
- Strong Python skills and software engineering fundamentals with infrastructure depth
- Familiarity with ML frameworks (PyTorch, Tensorflow or similar) is preferred
- Experience with cloud platforms such as AWS, GCP, or Azure, and familiarity with ML lifecycle tooling, including model registries and experimentation platforms
- Familiarity with inference optimization at the hardware and systems level
- Demonstrated ability to reason about tradeoffs between latency, cost, throughput, and reliability at the systems as well as operational level
- Experience in high-growth startup environments and an ability to thrive in a fast-paced, evolving technical landscape
Benefits
- Medical, dental, and vision coverage
- 401(k) plan
- Flexible PTO and company holidays
- Fully remote work within the United States
- Periodic company offsites and team gatherings
- Equity in the form of stock options