Software Engineer Infrastructure Storage (Senior)

Work set-up: 
Full Remote
Contract: 
Experience: 
Senior (5-10 years)
Work from: 

Offer summary

Qualifications:

Bachelor's or Master's degree in Computer Science or related field., At least 5 years of experience in storage systems software development., Strong programming skills in C, C++, Go, or Python., Deep understanding of storage protocols such as NFS, SMB, iSCSI, Fibre Channel, and S3..

Key responsibilities:

  • Design, develop, and maintain storage system software focusing on performance and scalability.
  • Implement and optimize storage protocol APIs for various access methods.
  • Develop distributed systems to manage storage resources across multiple solutions.
  • Troubleshoot complex issues in a production data center environment.

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Lambda SME https://lambdalabs.com/
51 - 200 Employees
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Job description

Were here to help the smartest minds on the planet build Superintelligence. The labs pushing the edge? They run on Lambda. Our gear trains and serves their models, our infrastructure scales with them, and we move fast to keep up. If you want to work on massive, worldchanging AI deployments with people who love action and hard problems, were the place to be.


If youd like to build the worlds best deep learning cloud, join us.


*Note: This position requires presence in our San Francisco, or San Jose office location 4 days per week; Lambda’s designated workfromhome day is currently Tuesday.


In the world of distributed AI training and inference, raw GPU and CPU horsepower is just a part of the story. Highperformance 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 highperformance AI clusters by welding together the latest in AI storage, networking, GPU and CPU hardware.

Our expertise lies at the intersection of:

  • HighPerformance 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 multitenant security and intelligent routing without compromising performance, using the latest in AI networking hardware.

  • Compute Clustering and Virtualization: We enable cuttingedge 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.

Required profile

Experience

Level of experience: Senior (5-10 years)
Industry :
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Troubleshooting (Problem Solving)
  • Collaboration

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