[Remote] Manager, Engineering - Hardware Acceleration (CUDA) at Torc Robotics

Ann Arbor, Michigan, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Autonomous Vehicles, Robotics, AutomotiveIndustries

Requirements

Master’s degree in Computer Science, Electrical Engineering, or related field
Experience leading software engineering teams (people management, hiring, coaching, performance management)
Strong technical expertise in CUDA, TensorRT, NVIDIA DriveOS, and embedded inference workflows
Deep proficiency in C++ and modern software development practices
Experience with ML frameworks such as PyTorch and ONNX for model export and optimization
Strong Linux development experience and familiarity with real-time, resource-constrained systems
Background working with safety-critical, automotive, or regulated environments
Ability to guide technical design decisions and challenge assumptions while fostering collaborative problem-solving
Comfortable working in an agile, fast-paced environment with shifting priorities

Responsibilities

Lead the development and optimization of ML inference pipelines on embedded hardware, including model conversion (PyTorch/ONNX), TensorRT integration, and CUDA-based pre/post-processing
Design, review, and guide development of custom CUDA kernels to support proprietary model layers and performance-critical operations
Drive technical execution across model optimization, inference scalability, benchmarking, and real-time system integration
Ensure high-quality C++ and CUDA code through robust design, documentation, and test coverage
Integrate optimized models and processing stages into Torc’s Application Engine and support Virtual Driver teams in adopting the optimized inference layer
Hire, lead, and develop a high-performance engineering team, building a culture of ownership, collaboration, and continuous improvement
Set technical and operational goals aligned with company-wide objectives; define and track team KPIs and milestones
Provide coaching, career development, and skill-building opportunities for engineers; maintain development plans and performance expectations
Establish and improve engineering processes for planning, delivery, testing, documentation, and cross-team collaboration
Reinforce Torc’s values through transparent communication, conflict resolution, and proactive change leadership

Skills

Key technologies and capabilities for this role

CUDATensorRTPyTorchONNXML inferenceembedded hardwaremodel optimizationdeep learning

Questions & Answers

Common questions about this position

What technical skills are required for the Manager, Engineering - Hardware Acceleration role?

The role requires deep technical knowledge across CUDA, TensorRT, and embedded ML deployment, along with experience in model conversion (PyTorch/ONNX), custom CUDA kernels, C++ code, and ML inference pipelines on embedded hardware.

What does the Hardware Acceleration team do at Torc Robotics?

The team builds the embedded inference foundation for Torc’s deep learning models on NVIDIA-based platforms, develops custom CUDA kernels and pre/post-processing pipelines, and delivers high-performance inference for the autonomy stack, working closely with Perception, Application Engine, Systems, and Hardware teams.

What leadership responsibilities does this engineering manager role involve?

The role involves hiring and leading a high-performance team, building a culture of ownership, collaboration, and continuous improvement, providing coaching and career development, setting technical goals and KPIs, and improving engineering processes.

Is this a remote position or does it require on-site work?

This information is not specified in the job description.

What is the salary or compensation for this role?

This information is not specified in the job description.

Torc Robotics

Develops autonomous driving technology for trucks

About Torc Robotics

Torc Robotics develops software systems for self-driving trucks, focusing on Level 4 autonomous driving technology that allows trucks to operate without human intervention in specific conditions. Their technology enhances road safety and meets the logistics industry's growing demands. Torc Robotics partners with major truck manufacturers, like Daimler Trucks, and collaborates with companies such as Luminar Technologies to integrate advanced sensors into their systems. They generate revenue by selling their software to fleet operators and truck manufacturers, while also providing ongoing support and updates. The company's goal is to improve efficiency and safety in freight transportation through their autonomous solutions.

Blacksburg, VirginiaHeadquarters

2005Year Founded

M_AND_ACompany Stage

Robotics & Automation, Automotive & TransportationIndustries

501-1,000Employees

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)

Company-wide holiday office closures

AD+D and Life Insurance

Risks

Increased competition from companies like Waymo and Aurora could impact market share.

Expansion into new markets involves significant operational costs and regulatory risks.

The strategic partnership with Daimler may limit alliances with other truck manufacturers.

Differentiation

Torc Robotics specializes in self-driving truck technology, focusing on Level 4 autonomy.

The company has a strategic partnership with Daimler Trucks for autonomous vehicle development.

Torc's modular products enable rapid integration of robotic systems for various applications.

Upsides

Torc is expanding operations to Texas and Michigan, enhancing market presence.

The company won the 2024 Top Software & Tech Award in the Robotics category.

Torc's focus on autonomous Class 8 trucks addresses aging workforce and rising demand.

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