Lambda’s GPU cloud is used by deep learning engineers at Stanford, Berkeley, and MIT. Lambda’s on-prem systems power research and engineering at Intel, Microsoft, Kaiser Permanente, major universities, and the Department of Defense.
If you’d like to build the world’s best deep learning cloud, join us.
What You’ll Do
- Architect, implement, and productionize large-scale high-performance storage systems for Lamda Cloud
- Optimize our storage infrastructure for machine learning workloads
- Drive storage performance analysis and observability
- Have designed large-scale (thousands of nodes) storage clusters for public clouds
- Have experience working with HPC (NVMe/RDMA) storage clusters
- Have deep understanding of both open source and proprietary storage systems
- Have extensive experience optimizing and tuning storage systems for specific workloads
- Have deep low level knowledge of Linux filesystems and storage drivers
- Have expertise in Ceph
Nice to Have
- Experience with NVIDIA GPUDirect Storage
- Experience with ML training workflows
- We offer generous cash & equity compensation. Cash Compensation Range: $208,000 – $282,000
- Investors include Gradient Ventures, Google’s AI-focused venture fund
- We are experiencing extremely high demand for our systems, with quarter over quarter, year over year profitability
- Our research papers have been accepted into top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG
- We have a wildly talented team of 115, and growing fast
- Our remote workforce, based on role, is across the U.S., with headquarters in San Francisco
- Health, dental, and vision coverage for you and your dependents
- Commuter/Work from home stipends
- 401k Plan
- Flexible Paid Time Off Plan that we all actually use
A Final Note:
You do not need to match all of the listed expectations to apply for this position. We are committed to building a team with a variety of backgrounds, experiences, and skills.
Equal Opportunity Employer
Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.