Senior Software Engineer, Data Science

GM-posted 2 days ago
Full-time • Senior
Hybrid • Warren, MI
5,001-10,000 employees
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Senior Software Engineer, Data Science Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to the Technical/Innovation Center in Warren (MI), Austin (TX), or Mountain View (CA) three times per week, at minimum. This position can be located at any of these locations. Why Join Us 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.

  • 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.
  • 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.
  • 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 offers a variety of health and wellbeing benefit programs.
  • Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.
  • This job may be eligible for relocation benefits.
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