Tesla
Internship, Machine Learning Engineer, Data Engineering & Analytics (Summer 2026)
Job description
What to Expect
Consider before submitting an application:
This position is expected to start May 2026 and continue through summer term (ending approximately August 2026 or later, if available). We ask for a minimum of 12 weeks, full-time (40 hours/week) and on-site, for most internships. Our internship program is for students who are actively enrolled in an academic program. Recent graduates seeking employment after graduation and not returning to school should apply for full-time positions, not internships.
International Students: If your work authorization is through CPT, please consult your school on your ability to work 40 hours per week before applying. You must be able to work 40 hours per week on-site. Many students will be limited to part-time during the academic year.
About the Team
The Data Engineering team is building a state-of-the- art analytics platform for business and operation intelligence. At Tesla, we have enormous amounts of data and we want to give meaning to it and help business users to make data driven decisions. Our platform will allow users to answer "what", "when" and "how" questions as well as allow them to ask "what if?”. Interns will help design, develop, maintain and support our Enterprise Data Warehouse & BI platform within Tesla. This position offers a unique opportunity to impact to the entire organization by creating a data driven culture.
What You'll Do
• Work with ML team and various other data scientists to create highly scalable API services that's based on ML and statistic models
• Influence API design and implementation for model inference services, ensuring scalable, reliable, and efficient integration of machine learning models into production systems
• Find new ways to improve in-house batch processing framework and workflow orchestration
• Work closely with other teams from across the organization and help them get end-to-end deployment on existing infra and to serve their model for real-time business use-cases
• Learn and execute on best practices in ML modeling, handling, and usage in an enterprise setting
What You'll Bring
• Currently pursuing a degree in Computer Science, Engineering or a related field of study and graduating in August 2026 - June 2027
• Able to work on site in Fremont, CA
• Prior academic training in Software Engineering with a focus on building and scaling batch and real-time infra
• Strong knowledge of Python, Airflow and SQL and comfort with data wrangling
• You have done production level model deployments and push a docker image to a API to serve ML models
• Transformer/VLM/LLM, CNNs, residual networks, GAN, clustering, sequence models) and frameworks/libraries (e.g., Tensorflow, PyTorch, Scikit-learn, Jax)
• Excellent experience in deployment of machine learning models in production environments, particularly in nlp/video/media-focused applications
Compensation and Benefits
Benefits
As a full-time Tesla Intern, you will be eligible for:
• Medical plans > plan options with $0 payroll deduction
• Family-building, fertility, adoption and surrogacy benefits
• Dental (including orthodontic coverage) and vision plans. Both have an option with a $0 payroll contribution
• Company Paid (Health Savings Account) HSA Contribution when enrolled in the High Deductible Medical Plan with HSA
• Healthcare and Dependent Care Flexible Spending Accounts (FSA)
• 401(k), Employee Stock Purchase Plans, and other financial benefits
• Company Paid Basic Life, AD&D, and short-term disability insurance (90 day waiting period)
• Employee Assistance Program
• Sick and Vacation time (Flex time for salary 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
• Commuter benefits
• Employee discounts and perks program
Expected Compensation
$40.00 - $56.00/hour + 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.
Tesla is also committed to working with and providing reasonable accommodations to individuals with disabilities. Please let your recruiter know if you need an accommodation at any point during the interview process.
Responsibilities
- Work with ML team and various other data scientists to create highly scalable API services that's based on ML and statistic models
- Influence API design and implementation for model inference services, ensuring scalable, reliable, and efficient integration of machine learning models into production systems
- Find new ways to improve in-house batch processing framework and workflow orchestration
- Work closely with other teams from across the organization and help them get end-to-end deployment on existing infra and to serve their model for real-time business use-cases
- Learn and execute on best practices in ML modeling, handling, and usage in an enterprise setting
Qualifications
- Currently pursuing a degree in Computer Science, Engineering or a related field of study and graduating in August 2026 - June 2027
- Able to work on site in Fremont, CA
- Prior academic training in Software Engineering with a focus on building and scaling batch and real-time infra
- Strong knowledge of Python, Airflow and SQL and comfort with data wrangling
- You have done production level model deployments and push a docker image to a API to serve ML models
- Transformer/VLM/LLM, CNNs, residual networks, GAN, clustering, sequence models) and frameworks/libraries (e.g., Tensorflow, PyTorch, Scikit-learn, Jax)
- Excellent experience in deployment of machine learning models in production environments, particularly in nlp/video/media-focused applications
Benefits
- You must be able to work 40 hours per week on-site
- Many students will be limited to part-time during the academic year
- Benefits
- Medical plans > plan options with $0 payroll deduction
- Family-building, fertility, adoption and surrogacy benefits
- Dental (including orthodontic coverage) and vision plans
- Both have an option with a $0 payroll contribution
- Company Paid (Health Savings Account) HSA Contribution when enrolled in the High Deductible Medical Plan with HSA
- Healthcare and Dependent Care Flexible Spending Accounts (FSA)
- 401(k), Employee Stock Purchase Plans, and other financial benefits
- Company Paid Basic Life, AD&D, and short-term disability insurance (90 day waiting period)
- Employee Assistance Program
- Sick and Vacation time (Flex time for salary 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
- Commuter benefits
- Employee discounts and perks program
- Expected Compensation
- $40.00 - $56.00/hour + 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
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