Solutions Architect - Hardware
Apply NowCompany: Lambda
Location: San Jose, CA 95123
Description:
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.
*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
You
Nice to Have
About Lambda
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.
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.
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 infrastructure
- 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 responsiveness
- Hyper-focused on customer satisfaction
You
- 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
- 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 efficient
- 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 workflows
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.