Engineering Manager, Deep Learning

Job Description

• As an Engineering Manager, you will lead the development and refinement of a cutting-edge perception system, leveraging deep learning for real-world applications. Your expertise in computer vision, deep learning, and team leadership will drive performance improvements and seamless integration across the company • Oversee the entire perception system development life cycle, from problem definition to deployment and ongoing improvement. • Lead a team of computer vision and perception engineers to develop and refine the system in a hands-on manner. • Spearhead the development of robust computer vision algorithms for object detection, tracking, semantic segmentation, and classification. • Champion the development and training of deep learning models for complex urban scene perception and real-time analysis. • Collaborate with cross-functional teams (cloud/device) for seamless integration and monitoring of perception models. • Analyze data to identify performance bottlenecks and opportunities for enhancing the perception system. • Foster automation in the improvement cycles of deep learning models used within the perception system. • Communicate technical findings and insights effectively to stakeholders across the company to drive performance improvements. • Utilize data visualization tools to present complex information clearly for informed decision-making.

Qualifications

• Ph.D. or Master's in Robotics, Machine Learning, Computer Science, Electrical Engineering, or a related field • 2+ years leading and managing teams focused on developing real-world computer vision and perception systems using deep learning on edge devices • Proven ability to deploy these systems with: • Deep Learning Frameworks: Expertise in PyTorch or TensorFlow (one mandatory, familiarity with both a plus) • Computer Vision Libraries: OpenCV • Deployment Optimization Tools: TensorRT • Strong Python programming and software design with experience in Pandas • Experience deploying DL models to run on real-world, resource-constrained, systems with a pragmatic approach towards problem-solving • Demonstrated proficiency in data science and traditional machine learning (SVMs, Random Forests). Prior experience with automated machine learning pipelines is desirable • Proven industry track record with experience in: • Automated data annotation for computer vision • Training multi-task and semi-supervised deep learning models for video data • Familiarity with designing multi-modal deep learning models incorporating temporal context and geometrical constraints is a plus

Benefits

• Options for 100% company paid medical, dental, and vision coverage for employees and dependents (for US employees) • Flexible Spending Account (FSA) and Dependent Care Flexible Spending Account (DCFSA) • Life, AD&D, Short and Long Term Disability Insurance • Aflac Critical Illness, Accident Insurance & Hospital Indemnity Insurance • MetLife Legal Plan(s) & Pet Insurance • Farmers GroupSelect Auto & Home Insurance • 401(k) with 3% company matching • Professional development reimbursement • Unlimited PTO • Hybrid work opportunities • Daily catered lunches in our San Francisco office