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 Jose 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.
In the world of distributed AI, raw GPU and CPU horsepower is just a part of the story. High-performance networking and storage are the critical components that enable and unite these systems, making groundbreaking AI training and inference possible.
The Lambda Infrastructure Engineering organization forges the foundation of high-performance AI clusters by welding together the latest in AI storage, networking, GPU and CPU hardware.
Our expertise lies at the intersection of:
High-Performance Distributed Storage Solutions and Protocols: We engineer the protocols and systems that serve massive datasets at the speeds demanded by modern clustered GPUs.
Dynamic Networking: We design advanced networks that provide multi-tenant security and intelligent routing without compromising performance, using the latest in AI networking hardware.
Compute Virtualization: We enable cutting-edge virtualization and clustering that allows AI researchers and engineers to focus on AI workloads, not AI infrastructure, unleashing the full compute bandwidth of clustered GPUs.
We are seeking a seasoned Storage Engineering Manager with experience in the specification, evaluation, deployment, and management of HPC storage solutions across multiple datacenters to build out a world-class team. You will hire and guide a team of storage engineers in building storage infrastructure that serves our AI/ML infrastructure products, ensuring the seamless deployment and operational excellence of both the physical and logical storage infrastructure (including proprietary and open source solutions).
Your role is not just to manage people, but to serve as the ultimate technical and operational authority for our high-performance, petabyte-scale storage solutions.Your leadership will be pivotal in ensuring our systems are not just high-performing, but also reliable, scalable, and manageable as we grow toward exascale.
This is a unique opportunity to work at the intersection of large-scale distributed systems and the rapidly evolving field of artificial intelligence infrastructure. This is an opportunity to have a significant impact on the future of AI. You will be building the foundational infrastructure that powers some of the most advanced AI research and products in the world.
Grow/Hire, lead, and mentor a top-talent team of high-performing storage engineers delivering HPC, petabyte-scale storage solutions.
Foster a high-velocity culture of innovation, technical excellence, and collaboration.
Conduct regular one-on-one meetings, provide constructive feedback, and support career development for team members.
Drive outcomes by managing project priorities, deadlines, and deliverables using Agile methodologies.
Drive the technical vision and strategy for Lambda distributed storage solutions.
You will lead storage vendor selection criteria, vendor selection, and vendor relationship management (support, installation, scheduling, specification, procurement).
Manage team in storage lifecycle management (installation, cabling, capacity upgrades, service, RMA, updating both hardware and software components as needed).
You will guide choices around optimization of storage pools, sharding, and tiering/caching strategies.
Lead team in tasks related to multi-tenant security, tenant provisioning, metering integration, storage protocol interconnection, and customer data-migration.
Guide Storage SREs in development of scripting and automation tools for configuration management, monitoring, and operational tasks.
Guide team in problem identification, requirements gathering, solution ideation, and stakeholder alignment on engineering RFCs.
Collaborate with the HPC Architecture team on drive selection, capacity determination, storage networking, cache placement, and rack layouts.
Work closely with the storage software teams and networking teams to execute on cross-functional infrastructure initiatives and new data-center deployments including integration of storage protocols across a variety of on-prem storage solutions.
Work with procurement data-center operations, and fleet engineering teams to deploy storage solutions into new and existing data centers.
Work with vendors to troubleshoot customer performance, reliability, and data-integrity issues.
Work closely with Networking, Compute, and Storage Software Engineering teams to deploy high-performance distributed storage solutions to serve AI/ML workloads.
Partner with the fleet engineering team to ensure seamless deployment, monitoring, and maintenance of the distributed storage solutions.
Stay current with the latest trends and research into AI and HPC storage technologies and vendor solutions.
Guide team in investigating strategies for using Nvidia SuperNIC DPUs for storage edge-caching, offloading, and GPUDirect Storage capabilities.
Work with the Lambda product team to uncover new trends in the AI inference and training product category that will inform emerging storage solutions.
Encourage and support the team in exploring new technologies and approaches to improve system performance and efficiency.
Experience:
10+ years of experience in storage engineering with at least 5+ years in a management or lead role.
Demonstrated experience leading a team of storage engineers and storage SREs on complex, cross-functional projects in a fast-paced startup environment.
Extensive hands-on experience in designing, deploying, and maintaining distributed storage solutions in a CSP (Cloud Service Provider), NCP (Neo-Cloud provider), HPC-infrastructure integrator, or AI-infrastructure company.
Experience with storage solutions serving storage volumes at a scale greater than 20PB.
Strong project management skills, leading high-confidence planning, project execution, and delivery of team outcomes on schedule.
Extensive experience with storage site reliability engineering.
Experience with one or more of the following in an HPC or AI Infrastructure environment: Vast, DDN, Pure Storage, NetApp, Weka.
Experience deploying CEPH at scale greater than 25PB.
Experience in serving one or more of the following storage protocols: object storage (e.g., S3), block storage (e.g., iSCSI), or file storage (e.g., NFS, SMB, Lustre).
Professional individual contributor experience as a storage engineer or storage SRE.
Familiarity with modern storage technologies (e.g., NVMe, RDMA, DPUs) and their role in optimizing performance.
Experience building a high-performance team through deliberate hiring, upskilling, planned skills redundancy, performance-management, and expectation setting.
Experience driving cross-functional engineering management initiatives (coordinating events, strategic planning, coordinating large projects).
Experience with NVidia SuperNIC DPUs for edge-caching (such as implementing GPUDirect Storage).
Deep experience with Vast, Weka and/or NetApp in an HPC or AI Infrastructure environment.
Deep experience implementing CEPH in an HPC or AI infrastructure environment at a scale greater than 100PB.
Experience driving organizational improvements (processes, systems, etc.)
Experience training, or managing managers.
The 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.
Founded in 2012, ~400 employees (2025) 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
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.
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.
Originally posted on Himalayas
Apply Now