Engineering Manager - Cloud

Lambda's GPU cloud is used by deep learning engineers at Stanford, Berkeley, and Carnegie Mellon. 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.

*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.

What You’ll Do

• Oversee the design, implementation, deployment, and operations of projects related to our cloud orchestration services
• Hire and grow a talented team of senior and staff level software engineers
• Lead projects from concept through production release, support, and maintenance
• Collaborate with fellow Engineering Managers and leadership to align your team’s work with company goals and customer needs
• Implement and support engineering best practices within the team (including code reviews, testing, etc) and drive operational excellence
• Assist the support team in resolving escalated technical issues
• Provide technical guidance and mentorship to foster a culture of continuous learning and growth

You

• BS/MS in Computer Science or a related field, or equivalent professional experience
• At least two years of engineering management experience, especially in a related application area, or experience in a Tech Lead role with a strong desire to grow into a management position
• At least seven years of software engineering or individual contributor experience, including at least two years of experience in Python, with significant exposure to designing, building, and maintaining large-scale, high-performance distributed systems
• Demonstrated experience managing teams in a high-growth startup environment
• Excellent interpersonal and communication skills with a proven ability to develop and maintain effective business relationships
• Strong problem solving and decision making skills, with a track record of successfully driving projects to completion
• Deep understanding of software and hardware concepts, including Linux kernel internals, systems programming, networking, storage, database systems, security
• Expertise in modern containerization and virtualization technologies, e.g. Docker, Kubernetes, KVM

Nice to Have

• Prior experience as a co-founder or early-stage startup team member
• Experience in the machine learning or computer hardware industry
• Proven track record of designing and implementing large scale cloud systems
• Deep understanding of algorithms, data structures, and performance optimization techniques

Salary Range Information 

Based on market data and other factors, the salary range for this position is $190,000 - $270,000. 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

• 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 300, and growing fast
• Health, dental, and vision coverage for you and your dependents
• Commuter/Work from home stipends for select roles
• 401k Plan with 2% company match
• 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.