Staff Systems Engineer

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

• Lead our efforts to deliver the world’s best platform for AI training, focusing on optimizing performance, resource utilization, and security across our Linux hypervisor fleet
• Design and implement fleet management best practices for maintaining a rapidly growing cloud platform, ensuring our host lifecycle management processes and systems scale with our growth
• Drive technical direction and quality of Lambda’s cloud infrastructure, and research new technical directions related to GPU virtualization and containerization for machine learning workloads

Qualifications

• 8+ years of in-depth Linux systems engineering, with a particular focus on virtualization and security with QEMU/KVM
• Have architected and implemented highly resilient systems for managing the life-cycle and configurations 10,000+ hosts
• Are expert-level with solutions for:
• SDDC (e.g. MAAS)
• Configuration management (e.g. ansible, salt stack)
• Host configuration lifecycle (e.g. foreman)
• Drift detection
• In-depth kernel-level understanding of Linux
• Strong engineering background - EECS preferred, Mathematics, Software Engineering, Physics
• Strong experience with containerization technologies like docker (Kubernetes is a huge plus!)

You will be successful in this role if you

• Have led and taken full ownership over large, ambiguous, cross team projects from conception to production
• Enjoy moving fast and making a large business impact
• Value working on a team of high performers that hold each other accountable
• Values building for the long term
• Are a self-starter, curious, and not afraid to ask when in doubt
• Are a quick learner and enjoy learning new technologies
• Value working on a low ego team that emphasizes strong communication, collaboration, and getting to the right answer as a team 
• Care deeply about well-tested code

Nice to Have

• Experience working in a startup
• Experience building and maintaining infrastructure for machine learning applications
• Experience with GPU virtualization

About Lambda

• We offer generous cash & equity compensation
• 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 130, and growing fast
• Our remote workforce, based on role, is across the U.S., with headquarters in San Jose, CA
• 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

Salary Range Information 

Based on market data and other factors, the salary range for this position is $190,000-$250,000. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description. 

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.