Manager, Engineering - Offline Perception

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.
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