Staff Software Engineer - Secondary Driving System

General Motors
Sacramento, CA, United States
about 1 month ago
Apply on dejobs.org
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Compensation
$218,800.0 - $335,300.0
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Data Analysis Systems Engineering Computer Vision C++ (Programming Language) Software Quality Code Review Continuous Integration Memory Management Middleware Python (Programming Language)
+15 more
Machine Learning Performance Tuning Regression Testing Sensor Fusion Software Engineering Systems Integration Strategies of Testing Data Logging Concurrency Information Technology ONNX (Open Neural Network Exchange) Format Machine Learning Operations TensorRT Feature Extraction C++14

Job description

As a Staff Software Engineer on the Secondary Driving System team within Embodied AI, you will:

  • 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 inperception, tracking, prediction, state estimation, localization, mapping, planning, controls, systems engineering, and safety to deliver robust, fail-operational behaviors for Super Cruise and future products.

What you’ll be doing

  • 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 upholdhigh standardsfor 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 andoptimizeSDS 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 SDSperceptionand 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 SDSperceptionand 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 andfacilitatedesign 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.

Requirements

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., * 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, includingsignificant experienceinperceptionand/or prediction.
  • Strongproficiencyin 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 ofperception, tracking, or prediction systems in real-time environments, including:
  • Multi-sensor fusion across camera, radar, and/or lidar (e.g., object-level fusion, occupancy/freespacefusion, 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)
  • Proventrack recordof 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 communicationand 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.

Bonus points

  • Experience building or leading camera/radar/lidar perception and fusion for autonomous driving or advanced driverassistancesystems in production.
  • Deepexpertisein 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.

Benefits & conditions

Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.

  • The salary range for this role is $218,800-$335,300. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
  • Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
  • Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

Benefits:

  • Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

About the company

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 believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team., General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on dejobs.org
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:19 min

Advancing autonomous driving capabilities with specialized software talent

Katrin Lehmann Katrin Lehmann +1 · Coffee With Developers

4:52 min

Essential phases in building and refining language models

Anshul Jindal Anshul Jindal +1 · World Congress 2025

1:18 min

Implementing routing middleware for seamless multi-fragment origination

Igor Minar Igor Minar +1 · World Congress 2025

10:40 min

Evaluating automotive software architectures and backend technologies

Georg Kühberger +1 · LIVE

2:32 min

Core libraries driving inference engines and multi-GPU networking

Adolf Hohl Adolf Hohl · World Congress 2024

4:19 min

Securing API requests with frontend interceptors and backend middlewares

Bartosz Pietrucha · JS Congress

Videos

See all

Related articles

See all