Software Engineer, MLOps, Manufacturing Quality

Description:
The Manufacturing Quality Data Engineering team specializes in predicting safety critical issues before they occur, protecting our customers. As part of Tesla's Vehicle Engineering organization, you'll have access to the data gold mine of design, manufacturing, and vehicle data sources, enabling you to design, develop, and deploy innovative generative AI and machine learning platforms globally. In this role, you'll focus on developing the machine learning operation infrastructure of the global machine learning platforms.

Responsibilities:
Design scalable system architecture for AI applications, including generative AI, time-series signal processing, and high-resolution curve platforms, to unblock key ML roadmap initiatives and support the end-to-end MLOps lifecycle
Build reliable, distributed infrastructure for ML and AI agents, emphasizing GPU-optimized environments and high-availability setups
Roll out advanced model versioning and A/B testing and evaluation frameworks to enhance AI agent performance and integration
Architect data pipelines and automation systems for efficient batch and real-time data handling from global sources, reducing deployment backlogs and improving scalability
Implement robust data storage solutions using relational, NoSQL, and graph databases to manage large-scale datasets for time-series and high-resolution curve data
Establish reliability standards in MLOps operations, with metrics for availability and uptime, while overseeing CI/CD, monitoring, and distributed training systems

Requirements:
Bachelor's Degree in Computer Science, Information Technology, or a related field, or equivalent experience
3+ years of work experience in software development
Experience with software engineering technologies, including Python, Docker, Kubernetes, MySQL, Microsoft SQL, MongoDB, Elasticsearch, Apache Kafka, and ETLs
Experience with machine learning frameworks and technologies, including Large Language Model, Retrieval Augmented Generation, LangGraph, TensorFlow, PyTorch, scikit learn, and graph neural networks
Strong attention to details and diligent in unit testing and integration testing practices
Experience working in a fast paced environment with many different projects

Compensation & Benefits:
Benefits

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

Expected Compensation
$140,000 - $252,000/annual salary + cash and stock awards + benefitsPay 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.