Lambda
What You’ll Do
Remotely deploy and configure large-scale HPC clusters for AI workloads (up to many thousands of nodes)
Remotely install and configure operating systems, firmware, software, and networking on HPC clusters both manually and using automation tools
Troubleshoot and resolve HPC cluster issues working closely with physical deployment teams on-site
Provide clear and detailed requirements back to other engineering teams on gaps and improvement areas, specifically in the areas of simplification, stability, and operational efficiency
Contribute to the creation of and maintenance of Standard Operating Procedures
Provide regular and well-communicated updates to project leads throughout each deployment
Mentor and assist less experienced team members
Stay up-to-date on the latest HPC/AI technologies and best practices
You
Are a deeply experienced HPC engineer comfortable with logical provisioning of a cluster
Have a strong understanding of HPC/AI architecture, operating systems, firmware, software, and networking
10+ years of experience in deploying and configuring HPC clusters for AI workloads
Have an innate attention to detail
Have experience with Bright Cluster Manager or similar cluster management tools
Are expert in configuring and troubleshooting:
SFP+ fiber, Infiniband (IB), and 100 GbE network fabrics
Ethernet, switching, power infrastructure, GPU direct, RDMA, NCCL, Horovod environments
Linux based compute nodes, firmware updates, driver installation
SLURM, Kubernetes, or other job scheduling systems
Work well under deadlines and structured project plans also knowing when and how to ask for changes to project timelines
Have excellent problem solving and troubleshooting skills
Have flexibility to travel to our North American data centers as on-site needs arise or as part of training exercises
Are able to work independently and as part of a team
Are comfortable mentoring and supporting junior HPC engineers on cluster deployments
Nice to Have
Experience with machine learning and deep learning frameworks (PyTorch, Tensorflow) and benchmarking tools (DeepSpeed, MLPerf)
Experience with containerization technologies ( Docker, Kubernetes)
Experience working with the technologies that underpin our cloud business ( GPU acceleration, virtualization, and cloud computing)
Keen situational awareness in customer situations, employing diplomacy and tact
Bachelors degree in EE, CS, Physics, Mathematics, or equivalent work experience
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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Remotely deploy and configure large-scale HPC clusters for AI workloads (up to many thousands of nodes)
Remotely install and configure operating systems, firmware, software, and networking on HPC clusters both manually and using automation tools
Troubleshoot and resolve HPC cluster issues working closely with physical deployment teams on-site
Provide clear and detailed requirements back to other engineering teams on gaps and improvement areas, specifically in the areas of simplification, stability, and operational efficiency
Contribute to the creation of and maintenance of Standard Operating Procedures
Provide regular and well-communicated updates to project leads throughout each deployment
Mentor and assist less experienced team members
Stay up-to-date on the latest HPC/AI technologies and best practices
You
Are a deeply experienced HPC engineer comfortable with logical provisioning of a cluster
Have a strong understanding of HPC/AI architecture, operating systems, firmware, software, and networking
10+ years of experience in deploying and configuring HPC clusters for AI workloads
Have an innate attention to detail
Have experience with Bright Cluster Manager or similar cluster management tools
Are expert in configuring and troubleshooting:
SFP+ fiber, Infiniband (IB), and 100 GbE network fabrics
Ethernet, switching, power infrastructure, GPU direct, RDMA, NCCL, Horovod environments
Linux based compute nodes, firmware updates, driver installation
SLURM, Kubernetes, or other job scheduling systems
Work well under deadlines and structured project plans also knowing when and how to ask for changes to project timelines
Have excellent problem solving and troubleshooting skills
Have flexibility to travel to our North American data centers as on-site needs arise or as part of training exercises
Are able to work independently and as part of a team
Are comfortable mentoring and supporting junior HPC engineers on cluster deployments
Nice to Have
Experience with machine learning and deep learning frameworks (PyTorch, Tensorflow) and benchmarking tools (DeepSpeed, MLPerf)
Experience with containerization technologies ( Docker, Kubernetes)
Experience working with the technologies that underpin our cloud business ( GPU acceleration, virtualization, and cloud computing)
Keen situational awareness in customer situations, employing diplomacy and tact
Bachelors degree in EE, CS, Physics, Mathematics, or equivalent work experience
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.
#J-18808-Ljbffr