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Solutions Architect - Hardware

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

  • 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

  • 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 Information 

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. 

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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Average salary estimate

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$162000K
$235000K

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What You Should Know About Solutions Architect - Hardware, Lambda

Join Lambda as a Solutions Architect - Hardware in the vibrant tech hub of San Jose, where our mission is to revolutionize AI computing. Since our inception in 2012, we've been a favorite among world-class engineers and researchers looking for cutting-edge GPU hardware and cloud solutions. In this role, you'll be the guru of our hardware offerings, transforming complex customer needs into tailor-made solutions. Collaborate closely with our sales team and use your expertise to recommend configurations that perfectly fit customer workflows while ensuring seamless deployments and satisfaction. You'll produce technical documents, engage with our internal community, and stay ahead of AI trends. With an agile spirit and a customer-first mentality, your work will help further our goal of making computation effortlessly accessible, just like electricity. Our company culture is vibrant and collaborative, and we’re looking for someone who’s eager to learn, innovative, and adaptable. If you are ready to make an impact in an exciting environment while helping engineers leverage AI technology, we want to hear from you!

Frequently Asked Questions (FAQs) for Solutions Architect - Hardware Role at Lambda
What are the primary responsibilities of a Solutions Architect - Hardware at Lambda?

As a Solutions Architect - Hardware at Lambda, your primary responsibilities include championing Lambda's innovative hardware solutions, becoming an expert in GPU-enabled workstations, collaborating with account executives to assess customer hardware requirements, and recommending optimal configurations to meet specific application needs. You will also develop technical documentation and support the sales process to ensure customer satisfaction.

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What qualifications are required for the Solutions Architect - Hardware position at Lambda?

Candidates for the Solutions Architect - Hardware position at Lambda should ideally have 4+ years in a product lead or solutions architect role focusing on hardware infrastructure. Experience with container orchestration platforms such as Kubernetes, and familiarity with NVIDIA's GPUs are essential. A background in ML/AI HPC and a proven ability to communicate technical requirements concisely will also set you apart.

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How does Lambda ensure customer satisfaction through the Solutions Architect - Hardware role?

Lambda ensures customer satisfaction through the Solutions Architect - Hardware role by emphasizing a deep understanding of client pain points and workflows. You'll be responsible for crafting solutions that align with customer needs and maintaining open communication throughout the deployment process, all while documenting designs and proposals that facilitate clear understanding and expectations.

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What is the work culture like for Solutions Architects at Lambda?

The work culture for Solutions Architects at Lambda is collaborative and geared towards continuous improvement. You’ll be part of a dynamic team where feedback is encouraged, and everyone contributes to the company's ambitious goals. Flexible hours and unique perks like generous PTO contribute to a supportive environment where work-life balance is prioritized.

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What growth opportunities are available for Solutions Architect - Hardware at Lambda?

Solutions Architects - Hardware at Lambda can expect numerous growth opportunities, including the potential to advance to higher technical or managerial positions. As the company grows and the demand for innovative solutions increases, you will have the chance to expand your skills and lead projects that directly contribute to Lambda’s mission in AI computing.

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Common Interview Questions for Solutions Architect - Hardware
Can you describe your experience with hardware infrastructure design?

In answering this, highlight specific projects where you designed or implemented hardware solutions, emphasizing the technologies you used and the outcomes. Be sure to connect this experience to how it would benefit Lambda and its client needs.

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How do you approach evaluating customer hardware requirements?

Discuss your methodology for gathering information from clients, such as conducting needs assessments and leveraging questions to uncover pain points and desired outcomes, illustrating how this informs your hardware recommendations.

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What is your experience with NVIDIA GPUs?

Detail your familiarity with NVIDIA GPUs, mentioning specific projects that utilized these technologies. Explain how your expertise will provide value in optimizing deployments for Lambda's customers.

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How do you stay updated on the latest trends in deep learning technologies?

Discuss the sources you rely on for industry knowledge, such as conferences, journals, or online communities. Mention how you apply insights gained to improve your work and benefit your team.

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Can you give an example of a challenging project you've worked on?

Share a specific instance where you faced a significant challenge in a project. Outline your approach to solving the problem and the successful outcome, demonstrating your problem-solving skills and resilience.

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How do you ensure effective communication with clients and team members on technical subjects?

Provide examples of how you've simplified complex technical information for better understanding. Discuss techniques you use to ensure everyone is on the same page, showcasing your communication expertise.

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Describe a time you had to adapt rapidly to changing client needs.

Discuss an instance where a client’s requirements changed unexpectedly. Highlight your ability to adjust your plans and recommendations to meet new demands while still achieving the project's objectives.

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What strategies do you use for maintaining documentation on your projects?

Talk about your practices for documenting projects, such as using structured formats and maintaining thorough records. Emphasize how this contributes to better collaboration and project success.

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How do you assess the effectiveness of a hardware solution after deployment?

Explain your approach to monitoring and evaluating the performance of hardware solutions post-deployment. Include how you gather feedback from clients and make necessary adjustments for improvement.

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Why do you want to work as a Solutions Architect - Hardware at Lambda?

Convey your passion for AI technology and how Lambda's mission aligns with your own professional goals. Talk about your enthusiasm for contributing to a company that is making significant strides in the AI computing space.

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Lambda provides Artificial Intelligence and Machine Learning infrastructure to companies like Apple, Intel, Microsoft, MIT, Harvard, the Federal Government, and the DOD. Were headquartered in the Dogpatch and are a short walk from the 22nd Street ...

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Full-time, hybrid
DATE POSTED
April 18, 2025

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