Senior, Engineering Manager - Perception & Auto-Tagging

About the Company  

At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight. Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.  

Meet the Team  

You'll lead the Offline Perception team within Data Loop and Simulation. The team explores the advantages of offline processing — building auto-labeling pipelines that combine different models and data-processing approaches to produce multi-modal, high-quality training data (2D, 3D, semantic segmentation, dense depth, and related modalities) that feeds online perception model development across Torc. You'll own strategy and execution for this data-to-model path, partnering with auto-tagging, data delivery, human annotation, and autonomy stakeholders on priorities, quality, and delivery.  

What You'll Do  

Lead, grow, and set technical direction for the Offline Perception team — hiring, mentoring, and managing the performance and career growth of engineers and ML engineers.

Own the roadmap for offline perception model development and evaluation, from curated datasets through training, benchmarking, and delivery to downstream consumers.

Stay technical enough to review and guide architecture decisions across auto-labeling integration, offline perception training and evaluation, and large-scale data pipeline design.

Represent the team to senior leadership and cross-functional stakeholders in perception, simulation, and systems — translating strategy into concrete execution plans.

Partner with product and peer engineering leaders (including auto-tagging, data delivery, and human annotation) to prioritize the roadmap and resolve cross-team dependencies.

Drive process and quality improvements across the offline perception lifecycle — dataset specs, evaluation methodology, and repeatable delivery of production-grade training data.

Manage team health and staffing, balancing headcount and skill mix between ML/perception engineering and data pipeline / AI infrastructure needs.  

What You'll Need to Succeed  

BS or MS in Computer Science, Robotics, Electrical Engineering, or a related field, plus 8+ years of software or ML engineering experience, including 2+ years managing engineers .

Hands-on experience with auto-labeling for self-driving development — not just model research, but pipelines that produce usable labels at scale.

Track record delivering large-scale perception datasets in production contexts — e.g. 2D OD, 3D OD, semantic segmentation, dense depth, and related modalities — with clear quality and delivery ownership.

Breadth across perception models and modalities — practical familiarity with different model families, what each is good for, and where they break down (accuracy, scale, latency, annotation cost, generalization).

Experience with AI infrastructure and data pipelines — distributed compute and data platforms (e.g. Databricks, Ray, Spark), cloud infrastructure (e.g. AWS), and the tooling needed to train and evaluate at fleet scale.

Proven track record leading and scaling technical teams, including hiring, mentoring, and performance management.

Experience setting technical strategy and roadmap for ML or data engineering teams, and communicating tradeoffs to senior leadership.

Strong communication skills, with the ability to represent team strategy to leadership and peer engineering teams.  

Bonus Points!  

Experience leading ML or data engineering teams in autonomous vehicles or robotics.

Familiarity with VLMs, auto-labeling pipelines, or perception model evaluation methodology.

Experience managing managers or leading multiple teams simultaneously.

Familiarity with scenario description standards such as Pegasus layers.  

Perks of Being a 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)

Company-wide holiday office closures

AD+D and Life Insurance  

At Torc, we're committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc'rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities. Even if you don't meet 100% of the qualifications listed for this opportunity, we encourage you to apply.  

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-102835 Hiring Range for Job Opening  US Pay Range $195,500 — $234,600 USD