The partner company is seeking to solve challenges in autonomous vehicle perception by developing machine learning models that accurately interpret and predict road and lane structures in complex environments.
Requirements
- Bachelor’s degree with 6+ years or Master’s degree with 3+ years of professional experience in Machine Learning Engineering, Autonomous Vehicles, Robotics, or a related field
- Strong expertise in 3D BEV space modeling, lane and road geometry, multi-camera calibration, and sensor projection
- Proficiency in Python and PyTorch, with experience translating research code into production-ready systems
- Hands-on experience with multi-modal sensor data (camera, LiDAR, radar) and data management pipelines
- Experience deploying and optimizing ML models for embedded and real-time systems
- Preferred: PhD in ML or Data Science, CUDA programming, custom PyTorch operations, publications in top-tier ML/Computer Vision conferences, experience with distributed training and multi-GPU systems
Responsibilities
- Develop and optimize computer vision algorithms for road and lane detection in monocular and multi-modal contexts
- Design and implement deep learning models for BEV (bird’s eye view) representations integrated into planning and control pipelines
- Analyze model performance, data distributions, and edge cases using advanced data science techniques
- Build efficient pipelines for large-scale data processing, annotation, augmentation, and domain adaptation
- Deploy and optimize ML models for real-time inference on automotive-grade hardware
- Collaborate cross-functionally with robotics, software, hardware, product, and operations teams to ensure seamless system integration
- Mentor junior engineers and contribute to the technical roadmap, staying current with the latest advancements in ML and computer vision
Other
- Bachelor’s degree with 6+ years or Master’s degree with 3+ years of professional experience
- Strong analytical, problem-solving, and communication skills, with a track record of mentoring or leading technical teams
- Flexible schedule and generous paid vacation, plus company-wide holiday closures
- Hybrid or remote work options available in the United States
- Collaborative, energetic, and team-focused work environment
