Product Engineering Leader: Device and Process Engineering

Atomic Machines is on Earth to radically advance humanity’s command over matter. Our mission is real-time bits-to-atoms manufacturing of anything at any scale, and to that end, we’re developing an entirely new digital micro-device manufacturing platform that is going to redefine how things are made, and do so while simultaneously enabling the rapid creation at any scale of new classes of machines – think medical micro-robotics, true lab-on-chip microfluidics, tunable antennas, ultrafast high-power and high-frequency RF switching devices and many more. The first device we are building with our platform has exceptional large-scale product/market fit and commercial traction, and we are pushing hard to share it with the world.

Our offices are in Berkeley and Santa Clara, California.

What You’ll Do:

• Develop and manage the end-to-end productization process, working closely with key stakeholders from initial concept to full-scale production, ensuring alignment with MC capabilities and strategic company goals.
• Create and maintain a comprehensive Performance Testing framework, continuously benchmarking product performance and leveraging real-time data to optimize outcomes and drive product improvements.
• Oversee the implementation of Reliability Testing protocols, ensuring products meet durability and lifecycle requirements prior to market release, with a focus on high-quality, reliable performance.
• Design and execute Accelerated Life Testing (ALT) programs, utilizing advanced machine learning tools to predict product longevity and enhance durability under a variety of conditions.
• Implement and refine a Continuous Improvement / Continuous Deployment (CI/CD) pipeline for product development, facilitating rapid iteration, deployment, and rollback of manufacturing processes with minimal disruption.
• Coordinate cross-functional efforts to integrate automated compliance and certification processes, ensuring that all products meet stringent quality and regulatory standards within the real-time manufacturing workflow.
• Lead the integration of Failure Mode and Effects Analysis (FMEA) into the manufacturing process, proactively identifying and mitigating potential risks to ensure robust and reliable product designs.
• Champion the use of AI-driven analytics and real-time data to optimize product development and manufacturing processes, ensuring each iteration builds on prior successes to achieve superior performance.

What You’ll Need:

• 10+ years of experience in product engineering and management, with a proven track record in overseeing the full product lifecycle, from concept to production. Experience with Micro-Electro-Mechanical Systems (MEMS) products is preferred.
• Advanced degree in a technical discipline such as Engineering or Physics. A Doctorate is preferred, particularly with a focus on reliability engineering, product lifecycle management, or advanced manufacturing techniques.
• Proven expertise in performance and reliability testing, including a deep understanding of Accelerated Life Testing (ALT), Failure Mode and Effects Analysis (FMEA), and reliability testing and modeling practices.
• Strong experience in managing Continuous Improvement / Continuous Deployment (CI/CD) pipelines, with a focus on rapid iteration, minimal disruption, and effective rollback strategies in a manufacturing environment.
• In-depth knowledge of product certification processes, with experience integrating compliance and certification processes into the manufacturing workflow to ensure that regulatory and quality standards are met.
• Leadership experience in building and managing cross-functional teams, with a minimum of 5 direct reports, and a commitment to fostering a collaborative and inclusive work environment.
• Exceptional communication and documentation skills, with the ability to clearly articulate complex technical concepts, produce high-quality documentation, and engage effectively with stakeholders at all levels.
• Creative and strategic thinking abilities, demonstrated through successful problem-solving, innovation, and effective leadership during whiteboard brainstorming sessions, driving clarity and alignment across teams.
• Autonomous and resilient work ethic, with the ability to make significant progress amidst ambiguity and rapidly changing priorities, ensuring that project milestones are met with precision and efficiency.

Bonus Points For:

• Experience with AI-driven analytics and machine learning tools, particularly in optimizing product development and manufacturing processes through data-driven decision-making and predictive modeling.