Manufacturing Test Manager

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.

Cerebras' current customers include global corporations across multiple industries, national labs, and top-tier healthcare systems. In January, we announced a multi-year, multi-million-dollar partnership with Mayo Clinic, underscoring our commitment to transforming AI applications across various fields. In August, we launched Cerebras Inference, the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services.

We are seeking an experienced Manufacturing Test Engineering Lead to lead our team of manufacturing test and test automation engineers. The successful candidate will be responsible for overseeing the development, implementation, and maintenance of test strategies, processes, and systems to ensure the quality and reliability of our products. This is a key leadership role that requires strong technical expertise, excellent communication skills, and the ability to motivate and manage a team of engineers.

Key Responsibilities:

• Lead and manage a team of manufacturing test and test automation engineers, providing guidance, coaching, and development opportunities to ensure their growth and success.
• Develop and implement comprehensive test strategies and plans to ensure product quality and reliability.
• Collaborate with cross‑functional teams, including design engineering, manufacturing, and quality assurance, to ensure test requirements are met.
• Lead the team to develop and implement test systems and processes for efficiency, reduce costs, and enhance product quality improvements.
• Collaborate with test automation and diagnostics team to design, develop, and deploy automated test solutions.
• Identify areas for process improvement and implement changes to optimize test efficiency, reduce cycle time, and improve product quality.
• Develop and track key performance indicators (KPIs) to measure test process effectiveness and efficiency.
• Provide technical guidance and expertise to the test engineering team, including troubleshooting and resolving complex test‑related issues.
• Develop and manage budgets for test engineering activities, including capital expenditures and operating expenses.
• Ensure effective utilization of resources, including personnel, equipment, and facilities.
• Communicate test plans, results, and issues to stakeholders, including management, design engineering, manufacturing, and quality assurance.
• Collaborate with other departments to ensure alignment and effective implementation of test strategies and processes.

Requirements:

• Bachelor's degree in Electrical Engineering, Computer Engineering, or a related field.
• 8+ years of experience in manufacturing test engineering.
• Proven track record of developing and implementing effective test strategies and processes for a manufacturing environment.
• Strong knowledge of test engineering principles, including test development, test automation, and test process improvement.
• Familiarity with industry‑standard test equipment and software, such as National Instruments, Agilent, or LabVIEW.
• Experience with automated test frameworks and programming languages, such as Python, C++, or Java.
• Excellent communication, leadership, and interpersonal skills.
• Ability to motivate and manage a team of engineers, providing guidance, coaching, and development opportunities.
• Strong problem‑solving and analytical skills, with the ability to troubleshoot complex test‑related issues.

The base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.

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