Responsibilities

• Lead the design and implementation of machine learning algorithms for automated component placement on printed circuit boards (PCBs).
• Engage in research to explore innovative techniques that enhance PCB design automation.
• Prototype and develop solutions, ensuring smooth transition from research to production.
• Collaborate closely with cross-functional teams, including electrical engineers and HPC specialists, to refine and optimize the component placement process.
• Maintain and upgrade the existing systems, troubleshoot issues, and enhance performance metrics.
• Contribute to a culture of continuous learning by sharing knowledge and insights with team members.

Requirements

• Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field with a strong focus on machine learning.
• Proven experience in developing and deploying machine learning models, preferably in the context of engineering or PCB design.
• Strong programming skills in Python, and familiarity with ML frameworks such as TensorFlow or PyTorch.
• Experience with high-performance computing (HPC) and optimization techniques.
• Ability to work collaboratively in a fast-paced, start-up environment while managing multiple projects.
• Excellent problem-solving skills and a passion for innovation in electrical engineering.

Benefits

• Competitive salary and equity options.
• Comprehensive health, dental, and vision insurance.
• Flexible work hours and remote work options.
• Opportunities for professional development and continuing education.
• Work in a supportive, dynamic team environment that encourages creativity and innovation.
• Join a mission-driven company focused on transforming the future of PCB design.