Staff ML Engineer – Scene Generation

This is a fully remote position, open to applicants in Michigan.

📋 Description

• Act as the technical lead for the team, responsible for key design choices and fostering consensus among engineers and stakeholders.

• Establish and oversee the technical vision and roadmap for the Scene Generation team’s Neural Rendering and generative modeling initiatives, aligning with Torc's AV 3.0 strategy.

• Manage the daily operations of the Scene Generation team, prioritizing tasks, removing obstacles for engineers, and making final decisions on architecture and technical approaches.

• Implement and guide the team in utilizing the most recent research advancements in Neural Rendering and generative models.

• Convert research findings into production-quality simulations for Camera, LiDAR, and Radar sensors, facilitating perception simulation and AV 3.0 training.

• Take full ownership of the neural rendering framework, from research and design through implementation, testing, cloud integration, and deployment.

• Integrate the framework within a cloud environment and automate pipelines to verify and validate autonomous-truck targets.

• Design, implement, test, and deploy production-quality software following disciplined development processes.

• Operate within the cloud machine learning ecosystem, managing integration and scaling decisions for the team’s pipeline.

• Evaluate capabilities, identify areas for improvement, and drive solutions that align with strategic and operational goals.

• Represent the Scene Generation roadmap, priorities, and constraints to peer teams and leadership.

• Mentor, coach, and develop engineers; engage in hiring, onboarding, and career progression activities.

⛳️ Requirements

• Bachelor's, Master's, or PhD in Computer Science, Robotics, Electrical Engineering, or a related technical discipline, with requisite experience: 10+ years for Bachelor's, 7+ years for Master's, or 5+ years for PhD.

• Alternatively, a PhD or equivalent work experience of 8+ years in a relevant field, with experience in shipping production software and leading technical teams.

• Strong proficiency in Python and deep learning frameworks such as PyTorch.

• Demonstrated expertise in Neural Rendering, including Neural Radiance Fields and 3D Gaussian Splatting.

• Proficient in generative models, including Diffusion Models and Flow Matching.

• Experience with production data in robotics and/or autonomous driving environments.

• Background in Computer Vision, Computer Graphics, 3D Reconstruction, or 3D Computer Vision.

• Experience managing autonomous-driving sensor data across multiple timestamps and modalities, including cameras, LiDAR, and radar.

• Recognized expertise with the capability to perform complex, high-impact tasks with minimal supervision.

• Familiarity with VDI and cloud-based machine-learning development environments.

• Proven experience in leading a team or acting as a technical lead.

• History of mentoring and developing engineers, including senior individual contributors.

• Ability to design, maintain, and take ownership of team technical solutions while driving organizational alignment.

• Bonus: Experience in autonomous-driving or robotics perception production.

• Bonus: Proficiency in CUDA programming.

• Bonus: Publications in top-tier conferences or journals in CV, AI, or Graphics.

• Bonus: Familiarity with MLOps and infrastructure tools such as Ray.

• Bonus: Experience with 3D labeling, calibration, and sensor simulation pipelines.

• Bonus: Formal people-management or technical lead experience.

🏝️ Benefits

• A competitive compensation package that includes a bonus component and stock options.

• Full coverage of medical, dental, and vision premiums for full-time employees.

• 401K plan featuring a 6% employer match.

• Flexible scheduling and generous paid vacation available immediately after the start date.

• AD+D and Life Insurance coverage.

• Potential sign-on bonuses, relocation assistance, and additional forms of compensation may be included in the total compensation package.