Job Summary:
Tesla's Energy Intelligence team is seeking a hands-on Sr. Machine Learning Engineer to architect and build production ML systems for energy telemetry. The role involves developing advanced ML frameworks for anomaly detection and predictive maintenance to enhance the performance of Tesla's energy products.
Responsibilities:
• Architect and deploy advanced ML systems for real-time anomaly detection, fault prediction, root cause analysis, and performance optimization across diverse energy telemetry streams (voltage, current, temperature, power output, efficiency metrics, etc.)
• Design physics-informed ML frameworks that combine domain knowledge from electrical and mechanical engineering with state-of-the-art data-driven techniques for superior model performance and generalization
• Build and scale production ML pipelines that process high-volume, multi-modal time-series data from millions of energy assets with sub-second latency and high reliability
• Develop interpretable AI systems that explain anomalies, predictions, and recommended actions to technical and non-technical stakeholders, enabling confident decision-making
• Create agentic AI workflows that autonomously detect, diagnose, prioritize, and recommend remediation for operational and maintenance challenges across global energy fleets
• Partner with data engineering, product, firmware, and service teams to define telemetry requirements, feature engineering strategies, model evaluation frameworks, and deployment architectures
Qualifications:
Required:
• Degree in Electrical Engineering, Mechanical Engineering, Physics, Computer Science, Applied Mathematics, or equivalent experience
• 3+ years of hands-on experience building and deploying production ML models, with strong focus on time-series analysis, anomaly detection, or predictive maintenance
• Deep expertise in ML frameworks and tools (PyTorch, TensorFlow, scikit-learn) and specialized time-series libraries (Prophet, NeuralProphet, GluonTS, tslearn, Kats)
• Strong programming skills in Python with proficiency in at least one compiled language (C++, Rust, Go) for performance-critical components
• Proven experience working with large-scale telemetry datasets, streaming data pipelines, and real-time inference systems
• Deep understanding of statistical methods for anomaly detection, forecasting, change point detection, and causal inference
• Strong technical communication skills - ability to explain complex ML concepts and collaborate effectively with cross-functional teams
• Background in energy systems - power electronics, battery management systems, inverter control, thermal dynamics, or grid operations with ability to encode domain physics into ML models
• Experience with edge ML and model optimization - quantization, pruning, and deployment on resource-constrained embedded systems
• Open-source contributions to ML frameworks, time-series libraries, or energy analytics tools
Company:
Tesla is an electric vehicle and clean energy company that provides electric cars, solar, and renewable energy solutions. Founded in 2003, the company is headquartered in Austin, USA, with a team of 10001+ employees. The company is currently Late Stage.