Lambda

HQ
San Francisco
750 Total Employees
Year Founded: 2012

Jobs at Lambda

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Recently posted jobs

21 Days AgoSaved
In-Office or Remote
4 Locations
Artificial Intelligence • Cloud • Machine Learning • Infrastructure as a Service (IaaS)
The Account CTO will be responsible for strategic technology leadership, defining technical strategies, and driving cloud transformation initiatives at an enterprise level while mentoring technical talent and influencing product strategy based on customer needs.
21 Days AgoSaved
In-Office or Remote
2 Locations
Artificial Intelligence • Cloud • Machine Learning • Infrastructure as a Service (IaaS)
The Senior Incident Manager leads incident response for AI infrastructure, coordinating teams to resolve critical incidents, conducting post-incident analysis, and improving operational resilience across systems.
22 Days AgoSaved
Remote
USA
Artificial Intelligence • Cloud • Machine Learning • Infrastructure as a Service (IaaS)
Owns technical customer deployments from contract through production readiness. Validates GPU, cloud, compute, storage, networking, and connectivity configurations; troubleshoots issues; coordinates Infrastructure, Engineering, Product, and Data Center teams; tracks risks and dependencies; provides status updates; guides onboarding; documents reusable runbooks; and serves as the customer’s technical contact until the environment is stable.
25 Days AgoSaved
In-Office or Remote
2 Locations
Artificial Intelligence • Cloud • Machine Learning • Infrastructure as a Service (IaaS)
Lead origination of PPAs, interconnection, and energy supply contracts for data centers. Build LCOE/NPV/IRR investment models, design and execute power and fuel hedges, structure hedging instruments, model demand charge and tariff impacts, forecast site-level energy costs, negotiate with utilities and suppliers, and monitor RTO/ISO market and regulatory developments.
One Month AgoSaved
Remote
USA
Artificial Intelligence • Cloud • Machine Learning • Infrastructure as a Service (IaaS)
Provide senior-level escalation and troubleshooting for GPU/HPC infrastructure, diagnosing hardware, driver, and kernel issues. Perform root-cause analysis across clusters, build automations and docs, mentor peers, collaborate with engineering for permanent fixes, and participate in on-call rotation and high-volume deployments.