Data Scientist Technical Lead - AI/ML

General Motors • Warren, MI

1d • Hybrid

About The Position

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 The Product Safety Data Analytics team is seeking a technical leader with an extensive hands-on experience in the full end to end data science lifecycle for artificial intelligence & machine learning. This technical leader role requires extensive programming and statistical techniques to both solve complex problems and provide guidance to a team of data scientists that are focused on AI/ML. If you're passionate about 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 an AI/ML Technical Lead, you will be responsible for working with our customers to understand their challenges and needs, develop new machine learning solutions, lead ML Ops in a cloud environment, develop proof of concepts for new generative AI solutions as well as providing technical expertise and guidance to a team of Data Scientists.

Requirements

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
• 7+ years of experience in machine learning, engineering, data science, or a related field
• 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 providing technical leadership in AI/ML
• 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

Nice To Haves

• 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
• Masters Degree in Computer Science, Engineering, Mathematics or related field
• 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
• Experience leading a team of data scientists to exceed customer expectations

Responsibilities

• 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
• 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.
• Challenge of determining the meaning of data and explaining how various teams and leaders can leverage it to improve and streamline their processes.
• Keeping defined structures in documentation and data and have a large toolset in statistical methodologies to tackle business problems.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees