Note: The job is a remote job and is open to candidates in USA. General Motors is redefining mobility through innovative vehicle experiences and advanced technology. As a Senior Machine Learning Engineer, you will develop and enhance ML perception models for the fallback autonomy stack, ensuring vehicle safety and reliability when primary systems fail.
Responsibilities
- Design, train, and evaluate ML perception models for object detection, semantic/instance segmentation, tracking, and short‑horizon prediction using multi‑modal camera, lidar, and radar data
- Develop and maintain the secondary stack perception model that enables the fallback autonomy system to safely bring the vehicle to a minimal risk condition when the primary system experiences a fault
- Define clear ML success metrics (e.g., precision/recall, latency, robustness under edge cases) and drive systematic experimentation to improve model performance against those metrics
- Analyze large‑scale datasets, curate challenging scenarios, and build data selection and labeling strategies that improve robustness for long‑tail and degraded‑sensor conditions
- Implement efficient training and inference pipelines, including model optimization techniques (e.g., pruning, quantization, distillation) to meet on‑vehicle compute and latency budgets
- Collaborate with software and infra engineers to integrate models into production systems, including interfaces, configuration, deployment, monitoring, and regression safeguards
- Partner with Safety, Systems Engineering, and Product to translate system requirements into concrete ML model requirements, metrics, and validation criteria
- Contribute to verification and validation strategies for the fallback perception model, including offline evaluation, simulation, hardware‑in‑the‑loop, and on‑road testing
- Participate in code reviews, promote ML and software engineering best practices, and provide technical mentorship to other engineers
Skills
- BS, MS, or PhD in Machine Learning, Robotics, Computer Science, or a related technical field; or equivalent practical experience building ML perception systems
- 3–5 years of experience developing ML solutions in perception, prediction, and/or autonomous driving or related domains
- Strong experience with multi‑modal sensor data (camera, lidar, radar), including data preprocessing, synchronization, and fusion
- Deep expertise in modern deep learning for perception, such as convolutional and transformer‑based architectures for: 2D/3D object detection, Semantic and instance segmentation, Multi‑object tracking and motion prediction
- Proficiency in at least one major ML framework (e.g., PyTorch, TensorFlow, JAX) and Python for model development, training, and analysis
- Solid software engineering skills, including experience working in C++ or similar languages in large, collaborative codebases
- Demonstrated ability to define ML metrics, design experiments, and systematically improve model performance and robustness
- Strong problem‑solving, communication, and cross‑functional collaboration skills
- Self‑motivated, with a passion for autonomous driving technology and its potential impact on safety and mobility
- Experience deploying ML models on embedded or resource‑constrained platforms, including model optimization and performance tuning for real‑time inference
- Experience with AV/ADAS perception stacks, robotics, or ROS
- Familiarity with safety‑critical systems and development practices
- Experience with large‑scale data pipelines, labeling workflows, and experiment management for ML
Benefits
- Benefit options include medical
- Benefit options include dental
- Benefit options include 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
- This job may be eligible for relocation benefits.
- Remote/Hybrid
- If you live within a 50-mile radius of Atlanta, Austin, Detroit, Warren, Milford or Mountain View, you are expected to report to that location three times per week, at minimum.
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