Meet the Team Torc is marching towards its AV 3.0 strategy. The Scene Generation team builds sensor simulation based on Neural Rendering and generative models for Torc's data-driven simulator. High-quality data from novel scenarios closes the domain data gap, solving one of the biggest challenges for safe autonomous driving. The team works on state-of-the-art approaches for Neural Rendering and data generation for camera, LiDAR, and Radar sensor data, contributing to Torc's data workflow for training and validation across the complete AV stack. As Staff ML Engineer, you will lead this team, setting its technical direction and day-to-day priorities.
What You'll Do - 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.
What You'll Need to Succeed - 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.
Bonus Points! - 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.
Perks of Being a Full-time Torc'r Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:
- 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
Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.
Job ID: R-102840
Hiring Range for Job Opening US Pay Range
$249,600-$299,500 USD
