Deep Learning Specialist at QuantumScape
San Jose, CA, US
Develop state-of-the-art deep learning solutions for analysis of high resolution, high velocity image data, leading to improved understanding of device performance and improved yield.
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.
Build deep learning pipelines that scale.
Develop and deploy edge machine learning solutions for high-throughput, automated manufacturing steps.
Develop and deploy machine learning and analytical solutions for data collected with cutting edge materials characterization equipment.
Remain up to date on advances in deep learning and machine learning methodologies and bring the most promising methods into use.
 
Knowledge, skills & abilities:
 
Share a passion for our mission.
Have a track record of building and deploying deep learning solutions in a materials research or manufacturing setting.
Thrive in a dynamic, technically-challenging environment, and quickly adapt to changes.
Enjoy working as part of a collaborative, multi-disciplinary team to tackle complex challenges.
Minimum requirements:
BS in Computer Science, Materials Science, Physics, Mechanical Engineering, Electrical Engineering, or related field.
At least 3 years of combined professional and academic experience applying deep learning to quantitative image analysis.
Competence with one or more deep learning frameworks (PyTorch, TensorFlow, Keras, fastai).
Fluency in one or more general programming languages, including but not limited to Python, C/C++.
 
Highly desired:
 
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.