Senior Software Engineer, Data Science

Senior Software Engineer, Data Science Job Description General Motors is at the forefront of transforming transportation through software-driven innovation. We’re driven by our bold vision of a future with Zero Crashes, Zero Emissions, and Zero Congestion. As we push forward into an era of vehicle intelligence and digital engineering, Artificial Intelligence and Data Science are a cornerstone of our strategy. Join a team at the forefront of innovation, where vehicle software design, release, warranty, and telemetry data converge to transform engineering and quality processes. We’re pioneering intelligent automation through advanced prognostics powered by smart algorithms, large language models (LLMs), and machine learning driving faster issue resolution and launching vehicles with exceptional quality. We’re looking for a Senior Software Engineer for Data Science to build scalable, AI-driven solutions that deliver measurable impact across engineering and customer experience. The Role As a Senior Software Engineer for Data Science, you will lead the development of scalable AI/ML powered analytics and prognostics applications in a cloud environment, driving innovation across vehicle telemetry and software integration domains. You’ll collaborate cross-functionally with engineers, data scientists, and domain experts to deliver high-impact solutions that improve vehicle quality and customer satisfaction. You will contribute to executive decision-making, product launch strategies, and data-driven quality improvements while staying ahead in a fast-paced, evolving tech landscape. What You’ll Do Prototype, and productionize scalable AI systems, with an emphasis on hybrid AI pipelines including LLMs. Lead AI/ML analysis of vehicle engineering and telemetry data ensuring robustness, interpretability, and physical relevance of outputs. Apply statistical methods, anomaly detection, and clustering to uncover patterns. Work with large scale data sets and collaborate with subject matter experts to incorporate physical interpretations of insights Leverage advanced data analytics and signal processing techniques to extract actionable insights from complex telemetry datasets Create interactive data visualizations to communicate and interpret complex data Design and build supervised and unsupervised ML models Develop and operationalize full-stack AI pipelines using MLOps practices (e.g., Docker, Kubernetes, FastAPI, MLFlow, cloud-native services). Define strategies for large-scale data ingestion, embedding generation, retrieval tuning, and prompt optimization in production environments. Ensure scalability, reproducibility, and performance of deployed models through well-defined evaluation, monitoring, and retraining mechanisms. Mentor junior level employees, providing coaching and guidance on difficult issues. Your Skills & Abilities (Required Qualifications) Bachelor’s in Computer Science, Engineering, Mathematics, or related field, or equivalent work experience 5+ years of experience building and deploying advanced machine learning or deep learning systems in production. Strong experience in Python, major ML frameworks (e.g., PyTorch, TensorFlow, HuggingFace Transformers), SQL, and signal processing libraries (PyWavelets, Tsfresh) Knowledge of ML modeling and toolsets (e.g. Scikit-learn, XGBoost for classification/regression tasks) Experience with MLOps tools and deploying models via containerized microservices on cloud platforms. Data Visualization using PowerBI, Databricks Apps, Azure Apps Exceptional analytical and independent problem-solving capabilities Strong listening and communication skills and ability to collaborate cross-functionally. Demonstrated ability to mentor junior level employees, providing coaching and guidance on difficult issues. What Will Give You a Competitive Edge (Preferred Qualifications) Master’s or PhD in Computer Science, Engineering, Mathematics, or related field 7+ years of experience building and deploying advanced machine learning or deep learning systems in production. Experience with retrieval-augmented generation (RAG), prompt engineering, and embedding optimization. Demonstrated expertise with LLMs, transformer architectures, AI agents Experience in automotive domain 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. Compensation:

The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position, as well as geography of the selected candidate. The salary range for this role is $134,000 - $205,000. Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance. Benefits: GM offers a variety of health and wellbeing benefit programs. 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. 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.

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