Staff Software Engineer – Secondary Driving System

General Motors•Sunnyvale, CA

2d•$218,800 - $335,300•Onsite

About The Position

At General Motors, our Embodied AI teams are redefining what’s possible in driver assistance and automated driving, combining human‑centered design with cutting‑edge robotics, optimization, and machine learning to build systems that are both intelligent and trustworthy. The Secondary Driving System (SDS) is an independent perception, planning, and controls stack that keeps the vehicle operating safely for a limited time if the primary driving system becomes unavailable. SDS requests driver takeover and, when needed, executes a Minimal Risk Maneuver (MRM) to bring the vehicle to a safe stop. We are looking for a Staff Software Engineer to provide technical leadership for the Secondary Driving System as a whole. This is a generalist software engineering role focused on building robust, production‑quality C++ software across the SDS stack (perception, tracking, prediction, planning, controls, and system integration). Depth in perception, tracking, prediction, or planning is highly preferred, but we are primarily looking for strong engineering and systems skills, with the flexibility to work where the team and product need you most.

Requirements

BS, MS, or PhD in Computer Science, Robotics, Electrical/Mechanical Engineering, or a related field; or equivalent practical experience.
8+ years of professional software engineering experience building production systems in robotics, autonomous vehicles, or other complex real‑time/control systems, including significant experience in perception and/or prediction.
Strong proficiency in modern C++ (e.g., C++14/17 or later) in large, multi‑contributor codebases; experience using Python for tooling, data analysis, and ML experimentation.
Demonstrated experience leading technical design and delivery of perception, tracking, or prediction systems in real‑time environments, including:
Multi‑sensor fusion across camera, radar, and/or lidar (e.g., object‑level fusion, occupancy/freespace fusion, early/late fusion architectures)
Classical computer vision and geometric algorithms (feature extraction, multi‑view geometry, stereo, SfM, SLAM/visual odometry)
Multi‑object tracking (Kalman/extended/unscented filters, track‑to‑track fusion, track lifecycle management)
Motion prediction for road users (analytical kinematic models, maneuver‑based prediction, or learned trajectory forecasting models)
Proven track record of delivering reliable, high‑quality robotics or autonomous driving software to production, including:
Testing strategies (simulation, HIL, scenario‑based testing, regression suites)
Robust metrics and dashboards for monitoring perception/prediction performance
Performance tuning under strict latency and compute budgets
Strong communication and collaboration skills, with the ability to:
Drive clarity in ambiguous technical spaces
Influence engineers and leaders across ML, systems, platform, hardware, and safety
Document and communicate complex technical concepts to diverse audiences
Passion for automated driving and robotics, and for building systems that measurably improve safety and driver experience.

Nice To Haves

Experience building or leading camera/radar/lidar perception and fusion for autonomous driving or advanced driver assistance systems in production.
Deep expertise in tracking and prediction for autonomous vehicles or robotics (e.g., interaction‑aware prediction, occupancy forecasting, scene‑level prediction).
Hands‑on experience with GPU/accelerator‑based ML inference, model deployment, and performance optimization (e.g., TensorRT, ONNX Runtime, custom accelerators).
Experience with safety‑critical software or working closely with functional safety teams on requirements, architectures, safety cases, and validation for fail‑operational features.
Background in ROS or similar robotics middleware, and familiarity with real‑time or embedded platforms and constraints.

Responsibilities

Serve as a technical lead for SDS software across multiple components of the stack, setting direction for algorithms, architectures, and system interfaces across features and releases.
Own the end‑to‑end technical strategy for key SDS behaviors and features, spanning perception/prediction integration, planning, controls, and system‑level interactions.
Balance hands‑on technical work with cross‑team leadership: you will still design and implement critical components in modern C++, while also guiding other senior and mid‑level engineers to deliver at scale.
Collaborate closely with experts in perception, tracking, prediction, state estimation, localization, mapping, planning, controls, systems engineering, and safety to deliver robust, fail‑operational behaviors for Super Cruise and future products.
Define technical vision & architecture: Set the technical direction for SDS software components with a focus on correctness, robustness, and predictable runtime behavior under tight latency and compute budgets.
Architect scalable, modular multi‑sensor perception pipelines for camera, radar, and lidar, including detection, classification, lane/road feature extraction, freespace/occupancy, and environmental context.
Establish and evolve interfaces and contracts between perception/prediction and upstream/downstream components (state estimation, localization, mapping, planning, controls, autonomy management).
Lead high‑impact projects: Lead design and delivery of multi‑object tracking systems (e.g., Kalman/extended/unscented filters, IMM, probabilistic data association, track lifecycle management) that provide stable, high‑quality tracks under real‑world noise and edge cases.
Drive development and integration of short‑horizon motion prediction for vehicles, VRUs, and other actors using a mix of analytical models and ML‑based forecasting, including uncertainty modeling that enables conservative, fail‑operational decisions.
Evaluate trade‑offs between traditional computer vision/robotics and ML‑based approaches, choosing the right tool for the problem and ensuring solutions are production‑ready under latency and compute constraints.
Hands‑on technical excellence: Design and implement critical components in modern C++ (C++17 or later), with careful attention to memory management, concurrency, and real‑time behavior; use Python for tooling, data analysis, and ML experimentation.
Set and uphold high standards for software quality: clean, well‑documented APIs; rigorous code reviews; automated and regression testing; continuous integration; and rich logging and observability for on‑road incidents.
Profile and optimize SDS components to meet strict runtime performance, determinism, and resource‑usage requirements, using offline and online evaluation frameworks and metrics to guide iteration, regression detection, and performance tuning.
Cross‑functional and safety alignment: Work with state estimation, localization, mapping, and autonomy management partners to ensure SDS perception and prediction behavior supports reliable engagement and MRM in response to primary stack failures.
Partner with Safety and Systems Engineering to ensure designs and implementations align with functional safety, redundancy, and MRM requirements for fail‑operational, eyes‑off features.
Represent SDS perception and prediction in cross‑org technical forums, ensuring alignment with broader autonomy, platform, and hardware roadmaps.
Leadership & mentorship: Provide technical mentorship to other engineers, from onboarding to growing senior and staff‑level talent in perception/tracking/prediction and modern C++.
Lead and facilitate design reviews, incident post‑mortems, and cross‑team technical deep dives, raising the bar for clarity, robustness, and execution speed.
Help build a healthy engineering culture: pragmatic, data‑driven decision‑making; strong ownership; and a focus on safety, reliability, and customer experience.