
10.000+ Mitarbeiter
Gegründet 1908
🚘 Automobilindustrie
🏭 Fertigung
🚗 Transport
💰 €500.000.000 Grant im 2024-07
Automotive • Manufacturing • Transport
General Motors ist ein führendes multinationales Unternehmen in der Automobilbranche und engagiert sich für eine Zukunft ohne Unfälle, ohne Emissionen und ohne Staus. Mit weltweiten Betrieben und Einrichtungen konzentriert sich GM auf Innovation in verschiedenen Bereichen, einschließlich Ingenieurwesen, Fertigung und Informationstechnologie. Das Unternehmen legt Wert auf Vielfalt, Inklusion und die Entwicklung nachhaltiger Technologien, um die Zukunft der Mobilität zu gestalten.
🕒 vor 26 Tagen
🇺🇸 Vereinigte Staaten – Remote
💵 $250.600 - $384.600 / Jahr
⏰ Vollzeit
🟠 Senior
🖥 Softwareentwickler
🦅 H1B-Visum-Sponsor
👻 Geisterscore 4%
🗣️🇺🇸🇬🇧 Englisch erforderlich
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+ Mitarbeiter
Gegründet 1908
🚘 Automobilindustrie
🏭 Fertigung
🚗 Transport
💰 €500.000.000 Grant im 2024-07
Automotive • Manufacturing • Transport
General Motors ist ein führendes multinationales Unternehmen in der Automobilbranche und engagiert sich für eine Zukunft ohne Unfälle, ohne Emissionen und ohne Staus. Mit weltweiten Betrieben und Einrichtungen konzentriert sich GM auf Innovation in verschiedenen Bereichen, einschließlich Ingenieurwesen, Fertigung und Informationstechnologie. Das Unternehmen legt Wert auf Vielfalt, Inklusion und die Entwicklung nachhaltiger Technologien, um die Zukunft der Mobilität zu gestalten.
• 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 • Report into the AV Safety Strategy and Assurance organization and influence launch decisions for next-generation automated driving products • Interpret ISO 21448 (SOTIF), ISO 5083, and AVSC best practices to define GM's strategy for safe autonomous system development, validation, and deployment • Own the behavior-focused portion of the ADS Safety Case, including claims, sufficiency criteria, and recommended evidence • Collaborate with Software Validation, Embodied AI, Simulation, and Safety Metrics teams on end-to-end AV behavior validation methodology • Set strategy for breaking down operational design domains and validating performance by behavior and in aggregate • Collaborate on evaluation metrics, human benchmarks, safety launch targets, and safety performance indicators • Assess AV performance using simulation, closed-course, and public-road data and provide prioritized feedback to engineering teams • Define and run an assurance process to verify sufficiency criteria and safety targets for launch readiness • Hire, lead, and develop a high-performing AV behavior safety engineering team • Set goals and expectations, coach and mentor team members, and grow technical depth in AV behavior safety, validation, and safety case development
• 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 in autonomous vehicle or robotics development or a related field • Demonstrated experience working on production-intent AV programs • Track record providing technical safety leadership in AV development • 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 influence cross-functional teams without direct authority • Strong problem-solving mindset, comfort with ambiguity, and proactive attitude toward learning and continuous improvement • 3+ years of people leadership experience, including hiring, leading, and growing high-performing technical teams • Preferred: Master's degree in Computer Science, Engineering, Mathematics, or related field • Preferred technical knowledge including 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, subject to motor vehicle report review • Remote work arrangement • Travel under 25%
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