In 2012, Lambda started with a crew of AI engineers publishing research at top machine-learning conferences. We began as an AI company built by AI engineers. That hasn't changed. Today, we're on a mission to be the world's top AI computing platform. We equip engineers with the tools to deploy AI that is fast, secure, affordable, and built to scale. Whether they need powerhouse GPU hardware on-site or the flexibility of cloud-based solutions, we've got the horsepower to make it happen. Lambda’s AI Cloud has been adopted by the world’s leading companies and research institutions including Anyscale, Rakuten, The AI Institute, and multiple enterprises with over a trillion dollars of market capitalization. Our goal is to make computation as effortless and ubiquitous as electricity.
If you'd like to build the world's best deep learning cloud, join us.Â
*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.
What You’ll Do
Champion Lambda's Hardware Solutions:
Become a subject matter expert in Lambda's GPU enabled workstations and servers,
Develop technical enablement materials (e.g., datasheets, application notes, performance benchmarks) for internal and external hardware-focused audiences.
Own the technical side of Lambda’s sales process.
Partner with account executives to evaluate customer hardware requirements,
Evaluate and assess customers needs to deeply understand pain-points, bottlenecks and expected outcomes
Recommend optimal hardware configurations in a cohesive solution to meet specific application, workflow, and performance needs.
Generate detailed technical Bills of Materials, ensuring successful hardware deployments and customer satisfaction.
Document proposal and designs in formats including but not limited to presentations, white-papers, diagrams, Bill of Materials and rack elevations
Demonstrate expertise in Lambda’s hardware infrastructureÂ
Build structured and purposeful learning into your work routine
Develop and support internal Lambda community as a subject matter expert
Be an expert at deploying AI/ML workloads on Lambda hardware solutions
Stay up to date on the latest deep learning trends, best practices and experiment with them using internal tools and resources
Develop high quality processes and documentation
Reinforce Lambda’s culture
Contribute positively throughout the organization
Maintain a high level of agility and responsivenessÂ
Hyper-focused on customer satisfaction
YouÂ
Love learning both broadly and deeply
Are a skilled communicator who can translate technical concepts into plain english from vague customer needs into technical requirements on the fly
Are comfortable communicating with and crafting presentation collateral for customers, both internal and external
Identify as a subject matter expert in the ML/AI HPC industry Â
Have 4+ years of experience as a product lead or as a solutions architect role supporting hardware infrastructure
Have 3+ years of experience designing, deploying and scaling hardware infrastructure
Have familiarity with container orchestration platforms like Kubernetes
Have experience working with NVIDIAs GPUs
Are a self-starter, curious, and not afraid to ask when in doubt
Measure yourself on results, not effort, and constantly seek to accomplish more by becoming more efficientÂ
Are able to build strong relationships across your entire organization
Have a proven mindset of never-ending improvement
Are comfortable in a an environment where customer’s needs, and the products that serve them, are continuously evolving
Nice to Have
Experience using deep learning frameworks such as TensorFlow or PyTorch
Experience designing, implementing and maintaining large-scale HPC infrastructure
Experience in operations management or Six Sigma methodology
Experience in defining and refining process workflowsÂ
About Lambda
We offer generous cash & equity compensation
Investors include Gradient Ventures, Google’s AI-focused venture fund
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
We have a wildly talented team of 200, and growing fast
Health, dental, and vision coverage for you and your dependents
Commuter/Work from home stipends
401k Plan with 2% company match
Flexible Paid Time Off Plan that we all actually use
Salary Range InformationÂ
Based on market data and other factors, the salary range for this position is (Base salary ranges from $162,000 to $235,000 plus variable sales target earnings). 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.Â
About Lambda
Founded in 2012, ~350 employees (2024) 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
Commuter/Work from home 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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