Principal AI/SOTIF Safety Engineer Technical Lead

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💎 Seniority level: Principal, 7+ years

📍 Location: United States

💸 Salary: 193600.0 - 296600.0 USD per year

🔍 Industry: Software Development

🏢 Company: careers_gm

🗣️ Languages: English

⏳ Experience: 7+ years

🪄 Skills: DockerLeadershipPythonSQLArtificial IntelligenceCloud ComputingData AnalysisJavaJava EEKubernetesMachine LearningMicrosoft AzureMLFlowNumpyPyTorchJiraTableauAlgorithmsData sciencePandasTensorflowCommunication SkillsAnalytical SkillsCollaborationAgile methodologiesRESTful APIsOrganizational skillsWritten communicationProblem-solving skillsTeamworkRisk ManagementData visualizationStrategic thinkingData modelingDebugging

Requirements:

7+ years of experience in machine learning, engineering, data science, or a related field of expertise
ISO 8800, ISO 24118 and other applicable industry standards and best practices for autonomous vehicles, aerospace and/or robotics.
Setting the strategy for E2E validation using techniques appropriate to validate AI models
Python, R, Java, PySpark, PyTorch, TensorFlow, Scikit-learn, LangChain, SQL
Large Language Models (LLMs), Generative AI, RAG, Deep learning, Reinforcement Learning, Natural Language Processing (NLP), SVM, XGBoost, Random Forest, Decision Trees, Clustering
Microsoft Azure (Data Lake, Machine Learning, Databricks)
MLflow, Model Monitoring & Versioning, Docker & Kubernetes, GitHub, Jira
Tableau, PowerBI, Pandas, NumPy
Proven track record providing technical safety leadership in AI/ML and AV development

Responsibilities:

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.
Work with software, data science and systems engineering teams to ensure GM safely trains new machine learning models to solve complex business problems.
Ensure continuity of safety as we enhance existing machine learning models to increase performance and adapt to our changing business landscape.
Set the safety standard for how we prototype, test and deploy new AI solutions, including Generative AI, to solve business problems.
Set the strategy for testing and validation of data sets and develop an assurance plan.
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.
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
Setup an assurance process to validate launch targets have been achieved

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