about 1 month ago
San Francisco, CA, USAMid Level / Senior
Base Salary
$183k - $310k/yr
Responsibilities
- Deploy and operate inference infrastructure for production ML workloads.
- Build and maintain vector database integrations for semantic search over multimodal robotics data.
- Design and implement evaluation and training infrastructure for model performance iteration.
- Own cloud architecture decisions affecting inference latency, throughput, cost, and reliability.
- Collaborate with product engineers to ship application-driven ML features.
- Identify and adapt off-the-shelf solutions for production needs.
Requirements
- Strong hands-on experience in production ML infrastructure and model serving optimization.
- Experience with technologies for building retrieval systems, including vector databases.
- Solid engineering fundamentals in distributed systems and cloud infrastructure.
- A bias toward application and product impact over research.
- Proven ability to operate independently and make effective tradeoffs.
- Excellent communication skills to explain ML tradeoffs to non-ML engineers.
Benefits
- $300 monthly budget for commuter benefits or workspace setup.
- Competitive equity grant in a Series B company.
- 100% medical, dental, vision, and term life insurance for employees.
- 401(k) matching up to 4%.
- 4 weeks vacation plus holidays and winter break.
- All expenses paid company off-sites twice a year.