Sr. Machine Learning Engineer, Energy Core Services, Digital Experience

Tesla Motors
Fremont, CA, United States
15 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Compensation
$124,000.0
Working hours
Regular working hours

Tech stack

LangGraph Framework Application Frameworks Computer Vision Big Data C Sharp (Programming Language) C++ (Programming Language) Software Code Optimization Computer Programming Information Engineering Data Visualization Python (Programming Language) Machine Learning
+19 more
Natural Language Processing RabbitMQ Power BI Tensorflow SQL Databases Tableau (Software) Data Storage Technologies Pytorch Large Language Models Model Validation Backend Build Management Scikit Learn Information Technology Apache Kafka Machine Learning Operations Software Version Control Data Pipelines Golang

Job description

You will build production-grade machine learning models and agentic SI workflows that detect issues, assess risk, forecast outcomes, and trigger automated actions across Residential Energy, Commercial Energy, Charging, and Solar Product & Service Engineering. Your work will reduce delays and rework, prevent failures, and transform how Tesla identifies and resolves issues before they affect customers. What You’ll Do

  • Train and deploy various types of machine learning models to production, including computer vision, NLP, and LLM-based models, that assist in understanding, detecting, or forecasting quality issues across Tesla Energy products and services
  • Design and build data storage and ingestion systems specifically for machine learning use cases
  • Complete statistical analyses to assist in understanding the occurrence rate, risk, and root cause of quality issues
  • Build and deploy infrastructure that supports scalable machine learning processes, including automated retraining, model versioning and evaluation, and low-latency real-time inference
  • Create agentic SI workflows that autonomously detect, diagnose, prioritize, and recommend remediation for operational challenges across Tesla Energy products and services
  • Build and maintain dashboards, data visualizations, and metrics using BI tools such as Tableau and Power BI, as well as in-product dashboards, to support modeling use cases and implementation
  • Assist business leaders in developing their strategy and quarterly planning through data-driven decisions, explaining model predictions and recommended actions to technical and non-technical stakeholders
  • Write unit and integration tests to ensure that code functionality requirements are met
  • Drive systems improvement by partnering with cross-functional software, data engineering, product, and operations teams to define data requirements, model evaluation frameworks, and deployment architectures

Requirements

  • 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, classification, or computer vision
  • Deep expertise in ML frameworks and tools (PyTorch, TensorFlow, scikit-learn) and LLM application frameworks (e.g., LangGraph)
  • Strong programming skills in Python and SQL, with proficiency in at least one compiled language (C#, Go, C++) for production backend services
  • Proven experience working with large-scale datasets, event-driven data pipelines (e.g., RabbitMQ, Kafka), and real-time inference systems
  • Deep understanding of statistical methods for anomaly detection, forecasting, root cause analysis, and causal inference
  • Strong technical communication skills - ability to explain complex ML concepts and collaborate effectively with cross-functional teams
  • Background in energy systems - solar, energy storage, power electronics, or grid operations - with ability to encode domain knowledge into ML models
  • Experience with model optimization and MLOps - quantization, automated retraining, model versioning, and production monitoring

Benefits & conditions

Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:

  • Medical plans > plan options with $0 payroll deduction
  • Family-building, fertility, adoption and surrogacy benefits
  • Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution
  • Company Paid (Health Savings Accounts) HSA Contribution when enrolled in the 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, AD&D
  • Short-term and long-term disability insurance (90 day waiting period)
  • Employee Assistance Program
  • Sick and Vacation time (Flex time for salary positions, Accrued hours for Hourly positions), and Paid Holidays
  • Back-up childcare and parenting support resources
  • Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance
  • Weight Loss and Tobacco Cessation Programs
  • Tesla Babies program
  • Commuter benefits
  • Employee discounts and perks program
  • Earned Wage Access: Real-time pay access paid daily, subject to eligibility and schedule (applicable for below Sr. Managers levels)

Expected Compensation $124,000 - $396,000/annual salary + cash and stock awards + benefits

Pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment. Tesla is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state or local laws.

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