Principal AI/SOTIF Safety Engineer Technical Lead (GPSSC)

Job Description

Remote: This role is categorized as remote. This means the successful candidate may be based anywhere in the United States and is not expected to report to a GM worksite unless directed by their manager.

Company Vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies."

The Role

The Safety Assurance for Effective Autonomous Driving Software (SAFE-ADS) department is part of the Global Product Safety, System, and Certification (GPSSC) organization at GM. This department serves as the central body for automated driving system (ADS) safety and brings together expertise from across the company to establish a comprehensive safety case. GM's vision is zero crashes, zero emissions, and zero congestion - AV safety is at the heart of driving forward this vision.

The AV Safety Strategy and Assessment team is seeking a technical leader with extensive experience in the full end to end development lifecycle for artificial intelligence & machine learning. As the AI Safety Principal Engineer, you will need to stay current on industry best practices and standards and guide the develop of GM's AI safety strategy. This technical leader role requires extensive programming and statistical techniques to solve complex problems, provide safety guidance to the engineering development teams that are focused on AI/ML, and assess their work products.

If you're passionate about safety, driving innovation through AI/ML and are a proven technical leader, this role offers an exciting opportunity to contribute to impactful projects in a dynamic team environment.

As the AI/ML Safety Technical Lead, you will be responsible for working with our partners and customers to define safety strategies and targets for AI/ML based autonomous driving systems, understand their challenges and needs, collaborate on new machine learning solutions, assess the safety of existing production models and ML Ops in a cloud environment, collaborate on proof of concepts for new generative AI solutions as well as providing safety expertise and guidance to a team of AI/ML developers. You will apply your experience with ISO 8800 and ISO 24118 to ensure we develop, deploy and maintain safe AI/ML systems in simulation, on closed course and on public roads.

What You'll Do (Responsibilities)

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  Referencing ISO 8800, ISO 24118 and AV industry best practices, develop the strategy for ensuring safe AI/ML and autonomous system development, deployment and maintenance.

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  Work with software, data science and systems engineering teams to ensure GM safely trains new machine learning models to solve complex business problems.

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  Ensure continuity of safety as we enhance existing machine learning models to increase performance and adapt to our changing business landscape.

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  Set the safety standard for how we prototype, test and deploy new AI solutions, including Generative AI, to solve business problems.

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  Set the strategy for testing and validation of data sets and develop an assurance plan.

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  Set the strategy for how we systematically break down operational design domain components and driving behavior components and how these are validated in aggregate and on a per behavior level.

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  Work with data science, systems engineering and software teams to set the strategy for how we establish safety launch targets across vehicle behaviors and in aggregate

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  Setup an assurance process to validate launch targets have been achieved

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This job is not eligible for relocation benefits. Any relocation costs would be the responsibility of the selected candidate

Additional Job Description

Your Skills & Abilities (Required Qualifications)

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  Bachelor's degree in Computer Science, Data Science, Human Factors, Machine Learning, Engineering, Mathematics, Physics, or a related field

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  7+ years of experience in machine learning, engineering, data science, or a related field of expertise

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  Looking for Extensive Experience in the flowing:

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  Machine Learning & AI Safety: ISO 8800, ISO 24118 and other applicable industry standards and best practices for autonomous vehicles, aerospace and/or robotics.

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  Validation of AI Driven Autonomous Systems: Setting the strategy for E2E validation using techniques appropriate to validate AI models

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  Programming & Frameworks : Python , R, Java, PySpark, PyTorch, TensorFlow, Scikit-learn, LangChain, SQL

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  Machine Learning & AI : Large Language Models (LLMs), Generative AI, RAG, Deep learning, Reinforcement Learning, Natural Language Processing (NLP), SVM, XGBoost, Random Forest, Decision Trees, Clustering

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  Cloud & Big Data Platforms: (Preferred Microsoft Azure (Data Lake, Machine Learning, Databricks)), Nice to Have (AWS (S3, SageMaker, Bedrock) or Google Cloud Platform (BigQuery, Dataflow, AI Platform) )

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  Deployment & MLOps: MLflow , Model Monitoring & Versioning, Docker & Kubernetes, GitHub , Jira

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  Data Analysis & Visualization : Tableau, PowerBI, Pandas, NumPy

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  Proven track record providing technical safety leadership in AI/ML and AV development

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  Excellent communication and collaboration skills, with the ability to work effectively in a team environment

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  Strong problem-solving mindset and a proactive attitude towards learning and self-improvement

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What Will Give You A Competitive Edge (Preferred Qualifications)

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  Masters Degree in Computer Science, Data Science, Machine Learning, Engineering, Mathematics, Physics, Aerospace, Aeronautics, Chemistry, or IT

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  10+ years of experience in machine learning, engineering, data science, or a related field of expertise

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  Extensive NLP solutions from business problem statement to deployment and ongoing optimization

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  Expertise with Large Language Models solutions from business problem statement to cloud deployment that have provided significant incremental business value

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  Experience with generative AI solutions that you have developed and deployed into a production environment that have provided significant incremental business value

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  Experience leading a team of data scientists to exceed customer expectations

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Compensation:

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  The expected base compensation for this role is $193,600- $296,600 USD Annually

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  Actual base compensation within the identified range will vary based on factors relevant to the position

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  Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance

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Benefits:

GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings