What are the responsibilities and job description for the Engineering Manager - Kubernetes position at Lambda?
In 2012, Lambda started with a crew of AI engineers publishing research at top machine-learning conferences. We began as an AI company built by AI engineers. That hasn't changed. Today, we're on a mission to be the world's top AI computing platform. We equip engineers with the tools to deploy AI that is fast, secure, affordable, and built to scale. Whether they need powerhouse GPU hardware on-site or the flexibility of cloud-based solutions, we've got the horsepower to make it happen. Lambda’s AI Cloud has been adopted by the world’s leading companies and research institutions including Anyscale, Rakuten, The AI Institute, and multiple enterprises with over a trillion dollars of market capitalization. Our goal is to make computation as effortless and ubiquitous as electricity.
If you'd like to build the world's best deep learning cloud, join us.
Based on market data and other factors, the annual salary range for this position is $285,000-$385,000. 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.
About Lambda
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.
Compensation Range: $285K - $385K
If you'd like to build the world's best deep learning cloud, join us.
- Note: This position requires presence in our San Francisco office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.
- Lead our world-class Kubernetes team, handling both internal and customer-facing projects and helping to set our future vision.
- Ensure our customers have the best possible experience across builds, handoffs, and support. Work directly with our largest customers to drive new feature discovery and strategic engagements.
- Manage both operational and development workloads, ensuring rigorous SLAs while also investing in automation and platform improvements to allow future growth.
- Own and assist with product-focused projects and strategies that keep Lambda at the cutting edge of GPU hosting, making us the best place to run any GPU, ML or AI workloads.
- Hire, grow and retain top-tier engineers, focusing on both systems reliability engineering and software engineering.
- Shape a culture of sustainable, empathetic, and high-velocity engineering, with a deep focus on cross-team collaboration, documentation, and data-driven decision-making.
- 6 years in a full-time management role at a high-growth technology company
- 10 years of industry experience in software engineering, with a focus on large-scale distributed systems and infrastructure.
- Proven record of leading and building engineering teams that work on mission-critical, high performance infrastructure and orchestration
- Exceptional leadership skills that encompass leading by trust, building empathy with your reports and other teams, and maintaining a sustainable but rapid velocity.
- Strong customer-facing skills, including pre-sales, general support, and incident management.
- Significant expertise in Kubernetes and cloud orchestration in general, including how systems are built and run in modern cloud environments.
- Demonstrated expertise in managing long-term projects alongside urgent, short-term priorities and incident resolution.
- Extensive experience collaborating with product, sales, and other engineering teams to build cohesive products with a focus on user experience and reliability.
- Ability to understand, review and structure Python and Go applications.
- Experience with bare-metal or low-level hardware management
- Experience managing a remote, globally-distributed team
- Experience deploying and operating HPC, ML or GPU applications
- Experience deploying Kubernetes or other orchestrators on bare metal
- Strong experience in Python and/or Go
- Significant sales, customer service or support experience
Based on market data and other factors, the annual salary range for this position is $285,000-$385,000. 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.
About Lambda
- Founded in 2012, ~350 employees (2024) and growing fast
- We offer generous cash & equity compensation
- Our investors include Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, US Innovative Technology, Gradient Ventures, Mercato Partners, SVB, 1517, Crescent Cove.
- 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
- Health, dental, and vision coverage for you and your dependents
- Commuter/Work from home stipends for select roles
- 401k Plan with 2% company match (USA employees)
- Flexible Paid Time Off Plan that we all actually use
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.
Compensation Range: $285K - $385K
Salary : $285,000 - $385,000