Senior, ML Engineer - Unstructured Environments

Torc Robotics is a leader in autonomous driving technology, now focused on developing software for automated trucks. They are seeking a Senior ML Engineer to develop next-generation perception models for complex environments, utilizing advanced AI techniques to enhance autonomous navigation capabilities.

Responsibilities:

• Develop and Optimize Computer Vision Algorithms
• Train monocular and multimodal terrain and road surface detection models
• Detect and classify objects, obstacles, traversable surfaces and environmental conditions
• Enhance perception systems to process multi-modal sensor data (camera, LiDAR, etc.) effectively
• Utilize data science techniques to analyze model performance, data distributions, and identify corner cases
• Contribute to BEV and 3D Perception Architectures
• Design and implement deep learning models for terrain and surface inference in BEV frameworks
• Integrate BEV representations into navigation and motion planning pipelines
• Data Management and Processing
• Develop efficient pipelines for large-scale data processing and annotation (pseudo-labeling) of sensor data (LiDAR point clouds, image frames)
• Implement data augmentation, synthetic data generation, and domain adaptation strategies to improve model robustness across diverse terrain types and environmental conditions
• Model Deployment and Optimization
• Deploy machine learning models on edge compute platforms, ensuring real-time performance and resource efficiency
• Optimize inference pipelines for embedded and ruggedized hardware platforms
• Cross-functional Collaboration
• Collaborate with robotics, software, and hardware engineers to ensure seamless integration of perception systems
• Work with technical leadership to define performance metrics and improve system reliability
• Research and Innovation
• Stay current with the latest advancements in computer vision, terrain modeling, BEV models, and autonomous navigation
• Translate scientific research into production-grade machine learning solutions for real
• Publish findings in top-tier conferences and journals (optional but encouraged)
• Leadership
• Contribute to the model development roadmap and provide strategic advice to technical leadership
• Mentor and guide junior team members to enhance their technical skills and career growth

Requirements:

• Bachelor's degree in Computer Science, Software Engineering, or related field with 6+ years of professional applied MLE engineering experience in Autonomous Vehicle, Robotics or related industry
• Master's degree in Computer Science, Software Engineering, or related field with 3+ years of professional applied ML engineering experience in autonomous systems, robotics, or a related industry
• Scientific understanding of machine learning for 3D BEV space modeling, including the ability to apply state-of-the-art ML research and methods in production environments
• Applied expertise in terrain and surface geometry modeling, multi-camera camera calibration, and sensor projection
• Experience analyzing data distributions and addressing long-tail edge cases
• Mastery of Python and PyTorch, with the ability to transition research-level code to production and deployment-ready standards
• U.S. Citizenship Requirement: This position requires access to information and systems that are restricted under U.S. law. Accordingly, only U.S. citizens are eligible for this role
• PhD in machine learning, computer vision, or data science
• Proficient in writing CUDA kernels and developing custom PyTorch operations
• Publications at top tier computer vision / machine learning conferences or journals (CVPR, ICCV, JMLR, IJCV, NeurIPS, IROS)
• Applied experience using Ray or similar frameworks to scale ML workloads across multi-node and systems for distributed training and experimentation
• Experience with perception systems operating in GPS-denied, GPS-challenged, or visually degraded environments