
10,000+ employees
Founded 1908
🚘 Automotive
🏭 Manufacturing
🚗 Transport
💰 $500M Grant on 2024-07
Automotive • Manufacturing • Transport
General Motors is a leading multinational corporation in the automotive industry, committed to creating a future with zero crashes, zero emissions, and zero congestion. With operations and facilities worldwide, GM focuses on innovation across various areas including engineering, manufacturing, and information technology. The company emphasizes diversity, inclusion, and the development of sustainable technologies to shape the future of mobility.
🔥 15 hours ago
🏄 California – Remote
💵 $250.6k - $384.6k / year
⏰ Full Time
🟠 Senior
🧑💻 Full-stack Engineer
🦅 H1B Visa Sponsor
👻 Ghost score 0%
AWS
Azure
Cloud
Docker
Google Cloud Platform
Java
Kubernetes
Numpy
Pandas
PySpark
Python
PyTorch
Scikit-Learn
SQL
Tableau
Tensorflow
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10,000+ employees
Founded 1908
🚘 Automotive
🏭 Manufacturing
🚗 Transport
💰 $500M Grant on 2024-07
Automotive • Manufacturing • Transport
General Motors is a leading multinational corporation in the automotive industry, committed to creating a future with zero crashes, zero emissions, and zero congestion. With operations and facilities worldwide, GM focuses on innovation across various areas including engineering, manufacturing, and information technology. The company emphasizes diversity, inclusion, and the development of sustainable technologies to shape the future of mobility.
• Lead the strategy and support execution for defining, measuring, and validating the safety of SAE Level 3–4 automated driving systems powered by machine-learned models • Reference and interpret ISO 21448 (SOTIF), ISO 5083, and AVSC best practices to define strategies for safe autonomous system development, validation, and deployment • Own the safety strategy for next-generation ADS architectures • Own the behavior-focused portion of the ADS Safety Case, including key claims, sufficiency criteria, and recommended evidence for AV behavior safety performance • Collaborate with Software Validation, Embodied AI, Simulation, and Safety Metrics teams to define end-to-end AV behavior validation methodology • Set the strategy for systematically breaking down ODDs and validating performance by behavior and in aggregate • Collaborate on evaluation metrics, human benchmarks, safety launch targets, and safety performance indicators for AV behaviors and overall system performance • Assess AV performance across safety and reliability dimensions using simulation, closed-course, and public-road data • Provide clear, prioritized feedback to engineering teams • Define and run an assurance process to verify sufficiency criteria and safety targets supporting launch readiness • Directly influence launch decisions for GM's next-generation automated driving products • Report into the AV Safety Strategy and Assurance organization
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field • 8+ years of experience in machine learning, engineering, data science, or a related field • 8+ years of experience in autonomous vehicle or robotics development or a related field • Demonstrated experience working on production-intent AV programs • Technical safety leadership experience in AV development, including safety strategies, risk assessments, validation methodologies, or safety case contributions • Deep understanding of AV behavior development, including ODDs, behaviors, evaluation criteria, and analysis of simulation, closed-course, and public-road test data • Experience applying AV safety standards and best practices, including ISO 5083, ISO 21448 (SOTIF), and AVSC practices • Excellent communication and storytelling skills • Ability to explain complex technical tradeoffs to executives and non-technical stakeholders • Ability to influence cross-functional teams without direct authority • Strong problem-solving mindset, comfort with ambiguity, and proactive attitude toward learning and continuous improvement • Master's degree in Computer Science, Engineering, Mathematics, or a related field preferred • Preferred technical experience with Python, R, Java, PySpark, PyTorch, TensorFlow, Scikit-learn, LangChain, SQL, LLMs, Generative AI, RAG, deep learning, reinforcement learning, NLP, SVM, XGBoost, Random Forest, Decision Trees, clustering, Microsoft Azure, AWS, Google Cloud Platform, MLflow, Docker, Kubernetes, GitHub, Jira, Tableau, Power BI, Pandas, and NumPy
• Bonus potential through an incentive pay program based on company performance, job level, and individual performance • Medical, dental, and vision benefits • Health Savings Account • Flexible Spending Accounts • Retirement savings plan • Sickness and accident benefits • Life insurance • Paid vacation and holidays • Tuition assistance programs • Employee assistance program • GM vehicle discounts • Company vehicle evaluation program, including assignment of a General Motors vehicle to drive and evaluate, subject to motor vehicle report review • Remote work arrangement • Travel requirement under 25%
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