Senior Machine Learning Engineer

Quick Facts

• Role: Senior Machine Learning Engineer (Energy Core Services, Digital Experience)

Description

Build and deploy production machine learning and agentic AI systems that analyze large volumes of multi-modal energy data to detect issues, assess risk, forecast outcomes, and trigger automated remediation across energy products and services. Train and deploy models (computer vision, NLP, and LLM-based), design ML data storage/ingestion, and deliver scalable low-latency inference with automated retraining and model governance. Create dashboards and statistical analyses to support data-driven decision-making and explain model predictions to technical and non-technical stakeholders.

Responsibilities

• Train and deploy computer vision, NLP, and LLM-based models for quality issue understanding, detection, and forecasting
• Design and build data storage and ingestion systems for ML use cases
• Perform statistical analyses for occurrence rate, risk, and root cause of quality issues
• Build and deploy infrastructure for scalable ML, including automated retraining, model versioning, evaluation, and low-latency real-time inference
• Create agentic AI workflows to autonomously detect, diagnose, prioritize, and recommend remediation for operational challenges
• Build dashboards and metrics using BI tools such as Tableau and Power BI
• Support business planning by explaining model predictions and recommended actions
• Write unit and integration tests
• Partner with software, data engineering, product, and operations teams to define data requirements, evaluation frameworks, and deployment architectures

Requirements

• Degree in Electrical Engineering, Mechanical Engineering, Physics, Computer Science, Applied Mathematics, or equivalent experience
• 3+ years building and deploying production ML models, with experience in time-series analysis, anomaly detection, classification, or computer vision
• Expertise in ML frameworks/tools: PyTorch, TensorFlow, scikit-learn; plus LLM application frameworks such as LangGraph
• Strong Python and SQL skills; proficiency in at least one compiled language (C#, Go, or C++) for production backend services
• Experience with large-scale datasets, event-driven pipelines (RabbitMQ, Kafka), and real-time inference systems
• Strong statistical understanding for anomaly detection, forecasting, root cause analysis, and causal inference
• Strong technical communication and collaboration skills
• Background in energy systems (solar, energy storage, power electronics, or grid operations)
• Experience with model optimization and MLOps (quantization, automated retraining, model versioning, production monitoring)

Benefits

• Medical plans with plan options and $0 payroll deduction
• Family-building, fertility, adoption and surrogacy benefits
• Dental and vision plans with options and $0 paycheck contribution
• Company-paid HSA contribution when enrolled in High-Deductible medical plan with HSA
• Healthcare and Dependent Care Flexible Spending Accounts (FSA)
• 401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits
• Company-paid Basic Life and AD&D; short-term and long-term disability insurance (90-day waiting period)
• Employee Assistance Program
• Sick and vacation time (flex time for salary roles), and paid holidays
• Back-up childcare and parenting support resources
• Voluntary benefits (critical illness, hospital indemnity, accident insurance, theft & legal services, pet insurance)
• Weight Loss and Tobacco Cessation Programs; Tesla Babies program
• Commuter benefits and employee discounts/perks