Senior Machine Learning Perception Engineer Fallback Driving System
Job Location:
Sunnyvale, CA - USA
Monthly Salary:
Posted:
Application Deadline:
Vacancies:
Job Summary
Job Description
At General Motors our product teams are redefining mobility. Through a human-centered design process we create vehicles and experiences that are designed not just to be seen but to be felt. Were turning todays impossible into tomorrows standard from breakthrough hardware and battery systems to intuitive design intelligent software and next-generation safety and entertainment features.
Every day our products move millions of peopleas we aim to makedriving safer smarter and more connected shaping the future of transportation on a global scale.
As a Senior Machine Learning Engineeronthe State Estimation and Mapping (SEAM) organization you will develop and improve the MLperceptionmodel that powers the secondary (fallback) autonomy stack for Super Cruise 3. You will focus on building robustperceptionfrom multimodalcamera lidar and radar data so the vehicle can safely bring itself to a stop when the primary autonomy stack is unavailable.
You will lead the design implementation and continuous improvement of ML models for object detection segmentation tracking and prediction working closely with partner teams acrossperception planning controls and safety.
What Youll Do
Design train and evaluate MLperceptionmodels for object detection semantic/instance segmentation tracking and shorthorizon prediction using multimodal camera lidar and radar data.
Develop andmaintainthe secondary stackperceptionmodel 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 largescale datasets curate challenging scenarios and build dataselectionand labeling strategies that improve robustness for longtail and degradedsensor conditions.
Implement efficient training and inference pipelines including model optimization techniques (e.g. pruning quantization distillation) to meet onvehicle 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 fallbackperceptionmodel including offline evaluation simulation hardwareintheloop and onroad testing.
Participate in code reviews promote ML and software engineering best practices and provide technical mentorship to other engineers.
Qualifications
BS MS or PhD in Machine Learning Robotics Computer Science or a related technical field; or equivalent practical experience building MLperceptionsystems.
35 years of experience developing ML solutions inperception prediction and/or autonomous driving or related domains.
Strong experience with multimodal sensor data (camera lidar radar) including data preprocessing synchronization and fusion.
Deepexpertisein modern deep learning forperception such as convolutional and transformerbased architectures for:
2D/3D object detection
Semantic and instance segmentation
Multiobject tracking and motion prediction
Proficiencyin 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 problemsolving communication and crossfunctional collaboration skills.
Selfmotivated with a passion for autonomous driving technology and its potential impact on safety and mobility.
Nice to have
Experience deploying ML models on embedded or resourceconstrained platforms including model optimization and performance tuning for realtime inference.
Experience with AV/ADASperceptionstacks robotics or ROS.
Familiarity with safetycritical systems and development practices.
Experience with largescale data pipelines labeling workflows and experiment management for ML.
Remote:This role is based remotely but if you live within a 50-mile radius of Atlanta Austin Detroit WarrenMilfordor Mountain View you are expected to report to that location three timesperweek at minimum.
Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paidin accordance withapplicable state laws. The compensation may not berepresentative for positionslocatedoutside of the California Bay Area.
The salary range for this role is $170600.00 to $261300.00. 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 incentivepayprogram offers payouts based on company performance job level and individual performance.
Benefits:
Benefits: GM offers a variety of health and wellbeing benefit options include medical dental vision Health Savings Account Flexible Spending Accounts retirement savings plan sickness and accident benefits life insurance paid vacation & holidays tuitionassistanceprograms employeeassistanceprogram GM vehicle discounts and more.
This job may be eligible forrelocationbenefits.
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Senior IC
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