Manufacturing QA Hardware Validation Engineer

Lambda Inc.; San Jose (CA); On-site; USD 100,000 - 130,000; Full time

Job summary

Join an innovative company on a mission to revolutionize AI computing. As a QA Engineer, you'll develop and maintain quality assurance processes for hardware manufacturing. This role involves comprehensive hardware validation, including performance testing and automation using Python. Collaborate with talented engineers to troubleshoot and resolve issues, ensuring that our products meet the highest quality standards. With a focus on continuous improvement and a commitment to excellence, this position offers a unique opportunity to contribute to cutting-edge technology in a dynamic and fast-paced environment. If you're passionate about quality and innovation, this is the perfect role for you.

Benefits

Health coverage

Dental coverage

Vision coverage

401k Plan with company match

Flexible Paid Time Off

Commuter/Work from home stipends

Qualifications

• Experience with Python scripting for QA automation.
• Hands-on experience with PXE server management.
• Skilled in GPU stress testing and hardware validation.

Responsibilities

• Develop and maintain QA processes for hardware manufacturing.
• Perform comprehensive hardware validation and testing.
• Collaborate with teams to troubleshoot product issues.

Skills

Python scripting

Analytical skills

Problem-solving

Troubleshooting

Vendor management

Tools

PXE server

Statistical process control (SPC)

Failure mode and effects analysis (FMEA)

Job 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 5 days per week.

What You’ll Do

• Develop, implement, and maintain QA processes specific to hardware manufacturing.
• Perform comprehensive hardware validation, including functional, performance, stress, and environmental testing.
• Write and maintain scripts (preferably in Python) to automate and improve QA testing processes.
• Manage PXE server setups for hardware deployment and testing environments.
• Conduct GPU stress testing, CPU performance evaluations, and validation of other hardware components.
• Create detailed and comprehensive documentation for all hardware validation processes and outcomes.
• Collaborate with design, engineering, and production teams to identify, troubleshoot, and resolve product issues early in the development and manufacturing lifecycle.
• Oversee quality standards across the supply chain, working closely with vendors and suppliers.
• Conduct failure analysis and recommend corrective and preventive actions to enhance product reliability.
• Perform regular audits of manufacturing processes to ensure adherence to quality standards.
• Drive root cause analysis for production issues and lead continuous improvement initiatives.

You

• Have experience with Python scripting for QA automation and improvement.
• Have hands-on experience with PXE server management and deployment.
• Are skilled in GPU stress testing, CPU performance testing, and hardware validation techniques.
• Possess a keen understanding of hardware manufacturing processes and quality assurance methodologies.
• Can create detailed documentation for validation procedures and outcomes.
• Are familiar with ISO standards, regulatory compliance, and industry best practices.
• Have excellent analytical, problem-solving, and troubleshooting skills.
• Communicate effectively and work well in cross-functional teams.

Nice to Have

• Experience in vendor management and supply chain quality control.
• Knowledge of statistical process control (SPC), failure mode and effects analysis (FMEA), and root cause analysis techniques.
• Certifications such as Six Sigma, Certified Quality Engineer (CQE), or similar.
• Familiarity with large language models (LLMs) and their applications in QA processes.
• Experience with additional scripting languages or automation tools.

Salary Range Information

Based on market data and other factors, the annual salary range for this position is $100,000-130,000. 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

• We offer generous cash & equity compensation.
• Investors include US Innovative Technology, Gradient Ventures, Mercato Partners, SVB.
• 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 350+, and growing fast.
• 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.