Lambda is the #1 GPU Cloud for ML/AI teams training, fine-tuning and inferencing AI models, where engineers can easily, securely and affordably build, test and deploy AI products at scale. Lambda’s product portfolio includes on-prem GPU systems, hosted GPUs across public & private clouds and managed inference services – servicing government, researchers, startups and Enterprises world-wide.
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.
Engineering at Lambda is responsible for building and scaling our cloud offering. Our scope includes the Lambda website, cloud APIs and systems as well as internal tooling for system deployment, management and maintenance.
What You’ll Do
Define Fleet Health metrics and indicators to objectively measure and improve system availability
Collaborate with the observability team on comprehensive monitoring and alerting systems to proactively predict, detect and respond to issues or anomalies
Create runbooks and automated remediations for common failure scenarios
Build in automation and auditing to ensure compliance and improve efficiency and productivity
Participate in on-call rotations and provide support for incident response and resolution
Implement and integrate logging and metrics across platforms such as Datadog, Prometheus, OpenTelemetry, Grafana, SumoLogic, etc
You
7+ years of experience in Site Reliability Engineering, DevOps, or a similar role
Strong understanding of modern AI infrastructure, from GPU architectures to hardware performance optimization
Strong understanding of Linux-based systems in a distributed environment
Solid understanding of Python and Go, with experience working with SWE teams to improve internal tooling.
Experience with monitoring and alerting tools (e.g., Prometheus, Grafana, SumoLogic)
Proficiency in automation and configuration management tools (e.g., Ansible, Terraform)
Familiarity with cloud platforms (e.g., OCI, AWS, GCP, Azure)
Excellent problem-solving and troubleshooting skills
Strong communication and collaboration skills
Passion for continuous improvement and innovation
Nice to Have
Experience in the machine learning or computer hardware industry
Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes)
Experience building and/or operating HPC resources.
Background in chaos engineering or similar reliability testing methodologies
Understanding of compliance frameworks (SOC 2, ISO 27001, etc.)
Salary Range Information
Based on market data and other factors, the annual salary range for this position is $255,000-$405,000. 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
Wellness and Commuter stipends for select roles
401k Plan with 2% company match (USA employees)
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.