Manager, Engineering - Hardware Acceleration (CUDA) job opportunity at Torc Robotics.

Torc Robotics Manager, Engineering - Hardware Acceleration (CUDA)

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Remote - U.S, ..........United States Of America

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 TeamThe Hardware Acceleration team builds the embedded inference foundation that enables Torc’s deep learning models to run efficiently and reliably on production AV hardware. Our mission is to convert and optimize perception and planning models for NVIDIA-based embedded platforms, develop custom CUDA kernels and pre/post-processing pipelines, and deliver deterministic, high-performance inference capabilities for the autonomy stack. We work closely with Perception, Application Engine, Systems, and Hardware teams to ensure that optimized models integrate seamlessly into Torc’s real-time autonomy platform. About the RoleWe are seeking an experienced and technically strong Engineering Manager to lead Torc’s Hardware Acceleration group. This leader will shape the technical roadmap for model optimization and embedded inference while growing and guiding a high-performing team of engineers. Success requires both deep technical knowledge across CUDA, TensorRT, and embedded ML deployment, and the leadership ability to coach, hire, set direction, and drive execution in a safety-critical environment. What You’ll Do 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. What You’ll Need to Succeed 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. Bonus Points Hands-on mentality — willing to jump into technical work when needed. Experience developing or certifying automotive-grade products (ISO 26262, ASPICE). Experience building middleware, model-serving frameworks, or GPU-accelerated systems. Background in high-performance computing, large-scale model optimization, or distributed inference systems. 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) 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: 102410

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Manager, Engineering - Hardware Acceleration (CUDA) job opportunity at Torc Robotics.

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