About the job

Enovix (Nasdaq: ENVX) is an advanced silicon battery company based in Fremont, Calif.

Enovix is on a mission to power the technologies of the future. Everything from IoT, mobile and computing devices, to the vehicle you drive, needs a better battery. Our disruptive architecture enables a battery with high energy density and capacity without compromising safety. We are scaling our silicon-anode, lithium-ion battery manufacturing capabilities to meet customer demand. For more information visit https://www.enovix.com/ and follow us on LinkedIn.

This is an exciting time at Enovix! We are looking for experienced candidates to help support our new lithium-ion battery production facility in Penang, Malaysia for commercialization of our 3D Silicon™ Lithium-ion Rechargeable Battery.

Job Summary:

We are looking for an Algorithm Engineer to support advanced battery manufacturing by developing data-driven and physics-informed algorithms that improve yield, quality, and throughput. This role focuses on leveraging manufacturing data, process signals, and inspection systems to optimize cell performance and enable scalable, high-volume production. The ideal candidate combines strong analytical skills with a deep interest in electrochemical systems and smart manufacturing.

Responsibilities:

• Develop and deploy algorithms for process optimization, defect detection, and yield improvement in battery manufacturing.
• Analyze high-dimensional datasets including formation data, cycling data, inline metrology, and sensor signals.
• Build machine learning and statistical models to predict cell performance, degradation, and failure modes.
• Design algorithms for early detection of defects such as internal shorts, misalignment, contamination, and structural inconsistencies.
• Collaborate with process, equipment, and cell design engineers to translate manufacturing challenges into algorithmic solutions.
• Support formation and aging optimization using data-driven modeling and parameter tuning.
• Develop computer vision algorithms for inspection of electrodes, stacking, and packaging processes.
• Implement predictive maintenance models for critical manufacturing equipment.
• Integrate algorithms into manufacturing systems for real-time decision-making.
• Conduct DOE (Design of Experiments) and validate algorithm performance on pilot and production lines.
• Document models, workflows, and performance metrics for continuous improvement.

Qualifications:

• Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, Mechanical Engineering, Materials Science, Applied Mathematics, or related field.
• 2–6+ years of experience in algorithm development, data science, or advanced manufacturing.
• Strong programming skills in Python (preferred), C++, or similar.
• Experience with machine learning libraries (e.g., Py Torch, Tensor Flow).
• Solid foundation in statistics, signal processing, and optimization techniques.
• Experience handling large datasets and working with tools like SQL, Pandas, Spark, or similar

Enovix in an equal opportunity employer