Lead Principal Machine Learning Engineer

$167,300 - $255,100/Yr

QuantumScape - San Jose, CA

Full-time - Senior

Hybrid - San Jose, CA

Electrical Equipment, Appliance, and Component Manufacturing

About the position

QuantumScape developed the industry's first anode-less cell design, which delivers high energy density while lowering material costs and simplifying manufacturing. Our innovative battery cell technology can store energy more efficiently and reliably than today's lithium-ion batteries. As a deep learning specialist on the metrology team, you will lead efforts to build and develop advanced methods for analyzing image and characterization data collected on our key components at high volume manufacturing scales!

Responsibilities

• Lead a team of machine learning engineers to develop state-of-the-art deep learning solutions for analysis of high-resolution, high-velocity image and measurement data, leading to improved understanding of device performance and improved yield.
• Establish standardized workflows for building, deploying, maintaining models.
• Serve as a machine learning expert/resource for the broader QuantumScape team.
• Collaborate closely with hardware and metrology teams building high-performance, automated inspection technologies, and a multi-disciplinary team of engineers and scientists developing novel materials and products.
• Collaborate with our software infrastructure team to build deep learning pipelines that scale.
• Develop and deploy edge machine learning solutions for high-throughput, automated manufacturing steps.
• Identify and manage external resources (contractors, software providers, consulting firms) to expand capacity or obtain new capabilities.
• Remain up to date on advances in deep learning and machine learning methodologies integrating the most promising techniques into our process.

Requirements

• BS in Computer Science, Materials Science, Physics, Mechanical Engineering, Electrical Engineering, or related field.
• At least 8 years of combined professional and academic experience applying deep learning for quantitative data analysis.
• 2+ years of experience leading or managing teams in this or a related field.
• Competence with multiple deep learning frameworks (PyTorch, TensorFlow, Hugging Face).
• Competence with Python data analysis stack (Pandas, scikit-learn).
• Previous experience with MLOps and leveraging Cloud (e.g. AWS, Google) resources.
• Fluency in one or more general programming languages, including but not limited to Python, C/C++.

Nice-to-haves

• Experience running and optimizing training, inference on multiple GPUs.
• Domain expertise in one or more areas related to manufacturing or physical sciences.
• Expertise in applying deep learning approaches for complex image segmentation and object detection.
• Experience applying edge-based and continuous data stream processing for near real-time inference.

Benefits

• Salary range for this role has a range of $167,300 to $255,100.
• Annual bonus.
• Generous RSU/Equity package.
• Employee paid health care.
• Employee Stock Purchase Plan (ESPP).