Manager, Engineering - App Engine (CUDA)

The Role

We are seeking a technically strong and people-focused Engineering Manager to lead our App Engine team. While this is not a hands-on coding role, deep technical expertise in GPU parallel computing, CUDA, and model deployment is essential. You will drive technical direction, prioritize execution, and grow a high-performing team responsible for building production-grade middleware.

Responsibilities

• Lead and grow a team building the application framework that integrates deep learning models into Torc’s autonomy stack.
• Drive technical execution across key focus areas: CUDA optimization, GPU resource management, model conversion pipelines (PyTorch, TensorRT, ONNX), and real-time system integration.
• Ensure reliability, determinism, and scalability across multi-sensor autonomous driving workloads.
• Partner with cross-functional teams (Perception, Planning, Systems, Validation, Hardware, Safety) to align technical direction and integration priorities.
• Mentor, coach, and develop engineers while cultivating a collaborative, high-trust team culture.
• Manage execution and delivery, balancing near-term goals with long-term architectural vision.
• Establish scalable processes for development, testing, and integration in a safety-critical environment.

Requirements

• Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, Robotics, or a related technical field.
• 3+ years of full-cycle people management experience.
• Deep technical expertise with CUDA, GPU parallel computing, and inference optimization.
• Strong proficiency in C++ and Linux-based development with knowledge of real-time systems.
• Experience with ML frameworks (PyTorch, TensorRT, ONNX) and model deployment pipelines.
• Proven leadership managing software engineering teams in complex, cross-functional environments.
• Strong understanding of system-level integration and safety-critical requirements.
• Able to thrive in a fast-paced, dynamic, and highly collaborative environment.
• Hands-on leadership style — comfortable diving into technical discussions and design reviews.
• Experience building or managing application/middleware frameworks for production AV or ADAS systems.
• Familiarity with ISO 26262, ASPICE, or other regulated safety standards.
• Background in distributed systems, high-performance computing, or large-scale data recording pipelines.

Qualifications

• Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, Robotics, or a related technical field.
• 3+ years of full-cycle people management experience.
• Deep technical expertise with CUDA, GPU parallel computing, and inference optimization.
• Strong proficiency in C++ and Linux-based development with knowledge of real-time systems.
• Experience with ML frameworks (PyTorch, TensorRT, ONNX) and model deployment pipelines.
• Proven leadership managing software engineering teams in complex, cross-functional environments.
• Strong understanding of system-level integration and safety-critical requirements.
• Able to thrive in a fast-paced, dynamic, and highly collaborative environment.
• Hands-on leadership style — comfortable diving into technical discussions and design reviews.
• Experience building or managing application/middleware frameworks for production AV or ADAS systems.
• Familiarity with ISO 26262, ASPICE, or other regulated safety standards.
• Background in distributed systems, high-performance computing, or large-scale data recording pipelines.

Skills

• Technical expertise in GPU parallel computing, CUDA, and model deployment.
• Leadership in managing software engineering teams in complex, cross-functional environments.
• Experience with ML frameworks (PyTorch, TensorRT, ONNX).
• Experience with CUDA, GPU parallel computing, and inference optimization.
• Strong proficiency in C++ and Linux-based development with knowledge of real-time systems.
• Experience with system-level integration and safety-critical requirements.
• Experience with ISO 26262, ASPICE, or other regulated safety standards.
• Experience with distributed systems, high-performance computing, or large-scale data recording pipelines.

Benefits

• Competitive compensation package including a bonus component and stock options.
• 100% paid medical, dental, and vision premiums for full-time employees.
• 401K plan with a 6% employer match.
• Flexible schedule and generous paid vacation (available immediately after start date).
• AD+D and Life Insurance.

Pay

• $160,800 - $193,000 USD