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.

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.
Ability to thrive in a fast-paced, dynamic, and highly collaborative environment.

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

Manager, Engineering – App Engine, CUDA

Key skills