Senior Site Reliability Engineer - Fleet Reliability

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.