Senior Software Engineer for Data Science at GM. Leading AI-driven analytics and prognostics applications for vehicle engineering and customer satisfaction.
Responsibilities
Lead the development of scalable AI/ML powered analytics and prognostics applications in a cloud environment
Drive innovation across vehicle telemetry and software integration domains
Collaborate cross-functionally with engineers, data scientists, and domain experts to deliver high-impact solutions
Prototype, and productionize scalable AI systems, emphasizing hybrid AI pipelines including LLMs
Apply statistical methods, anomaly detection, and clustering to uncover patterns
Work with large scale data sets and collaborate with subject matter experts
Create interactive data visualizations to communicate and interpret complex data
Develop and operationalize full-stack AI pipelines using MLOps practices
Mentor junior level employees, providing coaching and guidance on difficult issues
Requirements
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
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