About this role
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: Equipment Data Acquisition & Connectivity
• Develop and implement edge data acquisition solutions for manufacturing equipment. • Establish equipment communication standards for new equipment installations. • Integrate equipment with MES, HMI, PLC, SCADA, and other manufacturing systems. • Design and maintain equipment connectivity architecture across production lines. Manufacturing Data Infrastructure
• Build automated data collection pipelines to replace manual reporting processes. • Develop scalable data architecture for manufacturing analytics. • Ensure high-quality, reliable equipment operational data for business reporting. • Support data governance, standardization, and system integration. Manufacturing Analytics & AI
• Develop equipment monitoring and performance analytics. • Generate automated manufacturing KPIs including: • MTBA (Mean Time Between Assists) • MTBF (Mean Time Between Failures) • MTTR (Mean Time To Repair)
• Improve statistical reliability of manufacturing data. • Support variation analysis and statistical process monitoring. AI & Smart Manufacturing
• Deploy AI solutions for equipment monitoring and process optimization. • Support predictive analytics and anomaly detection. • Collaborate with manufacturing engineering teams to improve operational efficiency. • Support MLOps deployment and lifecycle management. Compliance & Standardization
• Establish equipment IT standards for future equipment purchases. • Support equipment calibration and cybersecurity compliance. • Develop operational standards and documentation for manufacturing data systems.
Qualifications:
• Bachelor's degree in Electrical Engineering, Electronics Engineering, Computer Engineering, Data Engineering, Computer Science, or related discipline. • Experience with manufacturing equipment integration and industrial communication. • Knowledge of PLC, HMI, MES, OPC-UA, Modbus, Ethernet/IP or similar industrial protocols. • Experience in manufacturing data acquisition and equipment connectivity. • Understanding of SQL, Python, or other data processing tools. • Knowledge of manufacturing KPIs and equipment performance analysis.
Preferred Qualifications
• Experience in battery, semiconductor, electronics, or automated manufacturing industries. • Experience with Industrial IoT (IIoT). • Knowledge of Edge Computing technologies. • Experience with AI/ML deployment in manufacturing. • Understanding of MLOps. • Experience with cloud-based manufacturing analytics. • Knowledge of statistical analysis and process optimization.
Preferred Skills
• Equipment Data Acquisition • Manufacturing Data Analytics • Edge Computing • Industrial Networking • AI Deployment • Manufacturing KPI Development • Data Architecture • Industrial Automation • Smart Factory • Process Optimization
Key Deliverables
• Automated equipment data acquisition system implementation • Standardized equipment connectivity architecture • Automated MTBA / MTBF / MTTR reporting • Manufacturing analytics dashboard development • Equipment IT standards for future production lines • AI-enabled equipment monitoring and optimization