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Software Engineer - Infrastructure Storage (senior)

Build scalable, high-performance storage systems for AI training and inference infrastructure
San Francisco, California, United States
Senior
$296,000 – 445,000 USD / year
3 days ago
Lambda

Lambda

A provider of high-performance GPUs for deep learning and AI research, as well as cloud services for machine learning workloads.

Senior Software Engineer

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.

In the world of distributed AI training and inference, 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
  • Dynamic Networking
  • Compute Clustering and Virtualization

AI training and inference relies on petabytes of data hosted on large, high-performance storage arrays. At Lambda, the Infrastructure Storage Team's job is to ensure that the data powering AI is fast, performant, and available across a variety of access protocols (fit for purpose).

We're looking for an experienced Senior Software Engineer to join our storage team. You'll join a team responsible for developing and implementing storage software for our next-generation on-premise storage solutions. This role requires expertise in distributed systems, and an in-depth understanding of file, block, and object storage protocols. You'll work on building scalable and resilient storage services that power our AI and machine learning infrastructure.

What You'll Do:

  • Design, develop, and maintain software for storage systems, focusing on performance, scalability, and reliability.
  • Implement and optimize storage protocol APIs for file (e.g., NFS, SMB), block (e.g., iSCSI, Fibre Channel), and object (e.g., S3) access.
  • Develop distributed systems for managing and orchestrating storage resources across multiple storage solutions and redundant arrays.
  • Collaborate with hardware and system architects to integrate software with various storage solutions, including NVMe and GPU-accelerated storage.
  • Troubleshoot and debug complex issues in a production data center environment.
  • Contribute to the full software development lifecycle, from requirements gathering and design to deployment and maintenance.

You Have:

  • Bachelor's or Master's degree in Computer Science or a related field.
  • 5+ years of experience in software development for storage systems.
  • Proven experience with distributed systems programming and concepts such as load balancers, data-durability, consensus algorithms, fault tolerance, and data consistency.
  • Strong programming skills in languages such as C, C++, Go, or Python.
  • Deep understanding of storage protocols, including:
    • File: NFS, SMB, Lustre
    • Block: iSCSI, Fibre Channel
    • Object: S3, Swift
  • Experience with Linux kernel internals and system-level programming.
  • Familiarity with containerization technologies like Docker and Kubernetes and running production workloads in these environments.
  • Familiarity with CI/CD and QA practices for distributed systems development environments.

Nice to Have:

  • Experience with AI/ML workloads and the unique storage challenges they present.
  • Knowledge of data center networking and high-speed interconnects (e.g., InfiniBand, RoCE).
  • Experience with performance tuning and optimization of storage systems.
  • Familiarity with hardware acceleration technologies, specifically GPUs and DPUs.

Salary Range Information

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.

About Lambda

  • 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

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.

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Software Engineer - Infrastructure Storage (senior)
San Francisco, California, United States
$296,000 – 445,000 USD / year
Software
About Lambda
A provider of high-performance GPUs for deep learning and AI research, as well as cloud services for machine learning workloads.