Senior Site Reliability Engineer - Fleet Reliability

Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU.If you'd like to build the world's best AI 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 DoDefine Fleet Health metrics and indicators to objectively measure and improve system availabilityCollaborate with the observability team on comprehensive monitoring and alerting systems to proactively predict, detect and respond to issues or anomaliesCreate runbooks and automated remediations for common failure scenariosBuild in automation and auditing to ensure compliance and improve efficiency and productivityParticipate in on-call rotations and provide support for incident response and resolutionImplement and integrate logging and metrics across platforms such as Datadog, Prometheus, OpenTelemetry, Grafana, SumoLogic, etcYou7+ years of experience in Site Reliability Engineering, DevOps, or a similar roleStrong understanding of modern AI infrastructure, from GPU architectures to hardware performance optimizationStrong understanding of Linux-based systems in a distributed environmentSolid 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 skillsStrong communication and collaboration skillsPassion for continuous improvement and innovationNice to HaveExperience in the machine learning or computer hardware industryKnowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes)Experience building and/or operating HPC resources.Background in chaos engineering or similar reliability testing methodologiesUnderstanding of compliance frameworks (SOC 2, ISO 27001, etc.)Salary Range InformationThe annual salary range for this position has been set based on market data and other factors. 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 LambdaFounded in 2012, with 500+ employees, and growing fastOur investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent CoveWe have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOGOur values are publicly available: https://lambda.ai/careersWe offer generous cash & equity compensationHealth, dental, and vision coverage for you and your dependentsWellness and commuter stipends for select roles401k Plan with 2% company match (USA employees)Flexible paid time off plan that we all actually useA 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 EmployerLambda 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 ... (truncated, view full listing at source)