[Hiring] Staff, ML Engineer - Scene Generation @Torc Robotics

Role Description

As Staff ML Engineer, you will lead the Scene Generation team, setting its technical direction and day-to-day priorities.

• Serve as the team's technical lead, owning key design decisions and driving consensus across engineers and stakeholders.
• Set and own the technical vision and roadmap for the Scene Generation team's Neural Rendering and generative modeling work, aligned to Torc's AV 3.0 strategy.
• Lead the Scene Generation team day to day, prioritizing work, unblocking engineers, and making the final call on architecture and technical approach.
• Implement and guide the team in applying the latest research advances in Neural Rendering and generative models.
• Translate cutting edge research into production quality Camera, LiDAR, and Radar sensor simulation that scales perception simulation and AV 3.0 training.
• Own the neural rendering framework end to end, from research, design, and implementation through testing, cloud integration, and deployment.
• Understand the integration of the framework in a cloud environment and automate the pipeline to scale target verification and validation of our autonomous trucks.
• Design, implement, test, and deploy shippable production quality software using disciplined software development processes, setting the technical bar for the team.
• Work within the cloud machine learning ecosystem alongside other machine learning services across the company, owning integration and scaling decisions for the team's pipeline.
• Proactively assess current capabilities to identify areas for improvement, proposing and driving solutions that align with core strategy and operations.
• Drive alignment across team interfaces to the rest of the organization, representing Scene Generation's roadmap, priorities, and constraints to peer teams and leadership.
• Mentor, coach, and grow engineers on the team, and play an active role in hiring, onboarding, and career development for the group.

Qualifications

• Bachelor’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 10+ years of experience.
• OR Master’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 7+ years of experience.
• OR PhD in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 5+ years of experience.
• Proficiency in Python and deep learning frameworks such as PyTorch.
• PhD or equivalent work experience of 8+ years in a relevant field (CS, Robotics, Electrical Engineering), with industry experience shipping production software and leading technical teams.
• Proven expertise in Neural Rendering (Neural Radiance Fields and 3D Gaussian Splatting) and generative models (Diffusion Models, Flow Matching).
• Experience with production data in the context of robotics and/or autonomous driving.
• Background in Computer Vision, Computer Graphics, 3D Reconstruction, or 3D Computer Vision.
• Experience handling autonomous driving sensor data across multiple timestamps and sensor modalities, including cameras, LiDAR, and radar.
• Recognized as an expert in the discipline, conducting complex, high impact work under minimal supervision and with wide latitude for independent judgment.
• Experience with VDI and cloud-based machine learning development environments.
• Demonstrated experience leading a team or serving as a technical lead, setting direction and driving consensus across engineers and stakeholders.
• Track record of mentoring and developing engineers, including more senior individual contributors.
• Proven ability to design, maintain, and own team technical solutions, and to drive alignment across team interfaces to the rest of the organization.

Requirements

• Experience with autonomous driving or robotics perception in production environments.
• Proficiency with CUDA programming for efficient rendering of large-scale scenes.
• Publications in top tier CV, AI, or Graphics conferences (CVPR, ECCV, ICCV, NeurIPS, ICLR, ICML, SIGGRAPH) or journals.
• Experience with MLOps and infrastructure tools such as Ray.
• Familiarity with 3D labeling, calibration, and sensor simulation pipelines.
• Prior experience as a formal people manager or tech lead.

Benefits

• A competitive compensation package that includes a bonus component and stock options.
• 100% paid medical, dental, and vision premiums for full-time employees.
• 401K plan with a 6% employer match.
• Flexibility in schedule and generous paid vacation (available immediately after start date).
• AD+D and Life Insurance.