AI/ML Data Scientist (GPSSC) at General Motors in Warren, MI

AI/ML Data Scientist (GPSSC) Location: Warren, Michigan, United States of America 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. We’re turning today’s impossible into tomorrow’s 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 people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale.. The Role Our Product Safety Data Analytics team is seeking an experienced AI/ML Data Scientist with hands-on experience in the full end to end data science lifecycle for artificial intelligence & machine learning. This role requires programming and statistical techniques to solve complex problems and work within a team framework on new AI/ML solutions. If you're passionate about driving innovation through AI/ML and have experienced delivering solutions to your customers, this role offers an exciting opportunity to contribute to impactful projects in a dynamic team environment. As an AI/ML Data Scientist, you will be responsible for working with our customers to understand their challenges and needs, develop new machine learning solutions, work with ML Ops in a cloud environment, develop proof of concepts for new generative AI solutions and Agentic AI solutions. What You’ll Do Work with our existing business partners to identify opportunities for new AI/ML solutions to enhance processes and enable our team members to be more efficient Train new machine learning models to solve complex business problems. Prototype new AI solutions, including Generative AI, to solve business problems. Develop new Agentic AI solutions to streamline business process Ehnance existing model solutions as business and technology continues to evolve Provide guidance on business problems using statistical methods and can craft ad-hoc reports to share findings and recommendations with business partners. Build statistical models that depict company-wide trends. Perform testing and validation of data sets. Work on and refine storytelling skills to convey ideas and results to leadership, customers and stakeholders Your Skills & Abilities (Required Qualifications) Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field 5+ years of experience in machine learning, engineering, data science, or a related field Looking for experience in the following: Programming & Frameworks: Python, R, Java,  PySpark, PyTorch, TensorFlow, Scikit-learn, LangChain, SQL Machine Learning & AI: Large Language Models (LLMs), Generative AI, RAG, Generative AI, Deep learning, Reinforcement Learning, Natural Language Processing (NLP), SVM, XGBoost, Random Forest, Decision Trees, Clustering Data Engineering: Databricks, Hadoop, SQL, Data Pipelines, Data Preprocessing & Feature Engineering 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) ) Deployment & MLOps:MLflow, Model Monitoring & Versioning, Docker & Kubernetes, GitHub, Jira Data Analysis & Visualization: Tableau, PowerBI, Pandas, NumPy Proven track record delivering AI/ML solutions to customers that get continued usage and drive value Excellent communication and collaboration skills, with the ability to work effectively in a team environment Strong problem-solving mindset and a proactive attitude towards learning and self-improvement What Will Give You A Competitive Edge (Preferred qualifications) Deep knowledge of GM’s Data Ecosystem Deep knowledge of GM’s Cloud Technology Stack for Data Science Deep knowledge of Global Product Safety’s SFI Process Extensive NLP solutions from business problem statement to deployment and ongoing optimization Expertise with Large Language Models solutions from business problem statement to cloud deployment that have provided significant incremental business value Experience with generative AI solutions that you have developed and deployed into a production environment that have provided significant incremental business value GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc). This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}. This job may be eligible for relocation benefits. About GM Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all. Why Join Us We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team. Benefits Overview From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources. Non-Discrimination and Equal Employment Opportunities (U.S.) General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers. 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