AI ML Engineering Internships
Ai ml engineering internships give university students, recent graduates, and early-career switchers hands-on project experience building and deploying machine learning models, mentorship from working engineers, and, at many employers, a path toward a full-time offer. Food & Beverage lead in internship volume, with TMEIC, Tesla, and ELUVIO among the employers posting roles now.
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Consider before submitting an application:
This position is expected to start August or September 2026 and continue through summer term (ending approximately December 2026) or continuing into Winter/Spring 2027 if available and there is an opportunity to do so. 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.
The Internship Recruiting Team is driven by the passion to recognize and develop emerging talent. Our year-round program places the best students in positions where they will grow technically, professionally, and personally through their experience working closely with their manager, mentor, and team. We are dedicated to providing an experience that allows the intern to experience life at Tesla by including them in projects that are critical to their team’s success.
The Tesla AI Hardware team is at the forefront of revolutionizing artificial intelligence through cutting-edge hardware innovation. Comprising brilliant engineers and visionaries, the team designs and develops advanced AI inference chips tailored to accelerate Tesla’s machine learning capabilities. The work of Tesla's AI Hardware team powers the neural networks behind Full Self-Driving (FSD), and Tesla humanoid robot, Optimus, pushing the boundaries of computational efficiency and performance. By creating custom silicon and optimized architectures, the team ensures Tesla remains a leader in AI-driven automotive and energy solutions, shaping a future where intelligent machines enhance human life.
As a key member of the Tesla AI hardware team, the AI/ML Modeling Engineering Intern will drive the modeling, and optimization of next-generation tensor compute hardware. This role requires deep expertise in computer architecture, and proven proficiency in performance modeling and optimization. The ideal candidate has a thorough understanding of AI workloads, and thrives in fast-paced environments, delivering elegant, high-performance solutions that push the boundaries of AI hardware efficiency.
What You'll Do
- Collaborate closely with system architects, micro architects, ML model designers, and compiler engineers to create highly efficient hardware designs on accelerated timelines
- Develop and validate sophisticated performance models to evaluate architecture and microarchitecture tradeoffs, guiding informed decision-making
- Define comprehensive workload suites and key performance metrics to benchmark and evaluate hardware capabilities
- Analyze and assess implementations of machine learning algorithms on Tesla AI hardware, identifying bottlenecks and opportunities for improvement
- Participate in hardware/software co-design efforts to align future hardware capabilities with evolving algorithmic demands
- Contribute to code reviews, testing, and debugging processes to maintain exceptional code quality and reliability
- Stay abreast of cutting-edge advancements in AI workloads, domain-specific languages, computer architecture, and simulation methodologies to inform strategic directions
What You'll Bring
- Currently pursuing a degree in Computer Science, Electrical Engineering, Computer Engineering, Applied Physics, or a related field with a graduation date between 2026 - 2027
- Expertise in Python + ML frameworks (PyTorch, TensorFlow, JAX)
- Experience with graph ML (e.g., PyG, DGL) for netlists and geometric data
- In-depth knowledge of Large Language Models (LLMs), transformer architectures, including their training, inference processes, and optimization techniques
- Strong expertise in CPU, GPU, and/or ML accelerator microarchitectures, with hands-on experience in performance characterization
- Robust programming skills in C/C++, Python, or other relevant languages
- Solid understanding of physical design constraints, including power, performance, and area (PPA) tradeoffs in hardware development
- Exceptional problem-solving abilities, capable of dissecting complex issues and devising innovative, practical solutions
- Excellent communication and interpersonal skills, fostering effective collaboration across teams, including leadership and engineering stakeholders
- Demonstrated experience in performance analysis, including the use of simulation frameworks and profiling tools
Compensation and 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
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.
Consider before submitting an application:
This position is expected to start August or September 2026 and continue through summer term (ending approximately December 2026) or continuing into Winter/Spring 2027 if available and there is an opportunity to do so. 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.
The Internship Recruiting Team is driven by the passion to recognize and develop emerging talent. Our year-round program places the best students in positions where they will grow technically, professionally, and personally through their experience working closely with their manager, mentor, and team. We are dedicated to providing an experience that allows the intern to experience life at Tesla by including them in projects that are critical to their team’s success.
The Tesla AI Hardware team is at the forefront of revolutionizing artificial intelligence through cutting-edge hardware innovation. Comprising brilliant engineers and visionaries, the team designs and develops advanced AI inference chips tailored to accelerate Tesla’s machine learning capabilities. The work of Tesla's AI Hardware team powers the neural networks behind Full Self-Driving (FSD), and Tesla humanoid robot, Optimus, pushing the boundaries of computational efficiency and performance. By creating custom silicon and optimized architectures, the team ensures Tesla remains a leader in AI-driven automotive and energy solutions, shaping a future where intelligent machines enhance human life.
As a key member of the Tesla AI hardware team, the AI/ML Modeling Engineering Intern will drive the modeling, and optimization of next-generation tensor compute hardware. This role requires deep expertise in computer architecture, and proven proficiency in performance modeling and optimization. The ideal candidate has a thorough understanding of AI workloads, and thrives in fast-paced environments, delivering elegant, high-performance solutions that push the boundaries of AI hardware efficiency.
What You'll Do
- Collaborate closely with system architects, micro architects, ML model designers, and compiler engineers to create highly efficient hardware designs on accelerated timelines
- Develop and validate sophisticated performance models to evaluate architecture and microarchitecture tradeoffs, guiding informed decision-making
- Define comprehensive workload suites and key performance metrics to benchmark and evaluate hardware capabilities
- Analyze and assess implementations of machine learning algorithms on Tesla AI hardware, identifying bottlenecks and opportunities for improvement
- Participate in hardware/software co-design efforts to align future hardware capabilities with evolving algorithmic demands
- Contribute to code reviews, testing, and debugging processes to maintain exceptional code quality and reliability
- Stay abreast of cutting-edge advancements in AI workloads, domain-specific languages, computer architecture, and simulation methodologies to inform strategic directions
What You'll Bring
- Currently pursuing a degree in Computer Science, Electrical Engineering, Computer Engineering, Applied Physics, or a related field with a graduation date between 2026 - 2027
- Expertise in Python + ML frameworks (PyTorch, TensorFlow, JAX)
- Experience with graph ML (e.g., PyG, DGL) for netlists and geometric data
- In-depth knowledge of Large Language Models (LLMs), transformer architectures, including their training, inference processes, and optimization techniques
- Strong expertise in CPU, GPU, and/or ML accelerator microarchitectures, with hands-on experience in performance characterization
- Robust programming skills in C/C++, Python, or other relevant languages
- Solid understanding of physical design constraints, including power, performance, and area (PPA) tradeoffs in hardware development
- Exceptional problem-solving abilities, capable of dissecting complex issues and devising innovative, practical solutions
- Excellent communication and interpersonal skills, fostering effective collaboration across teams, including leadership and engineering stakeholders
- Demonstrated experience in performance analysis, including the use of simulation frameworks and profiling tools
Compensation and 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
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.
AI ML Engineering Internship Market
Who's Hiring
Top Industries Hiring
- Food & Beverage
Tips for Your AI ML Engineering Internship Search
Apply in the fall for summer cohorts
Large technology companies and enterprise employers open summer ai ml engineering internship recruiting as early as August or September the year before. Smaller companies and co-op programs post much closer to start dates. Checking listings consistently through fall and winter means you reach both recruiting cycles without missing early deadlines.
Build a public portfolio before you apply
For ai ml engineering internships, a public GitHub repository with two or three documented projects carries more weight than a long list of coursework. Each project should show the dataset, the model or pipeline you built, the tools used, and the outcome. Recruiters screen candidates by clicking the link, so make sure every repository has a clear README.
Work campus channels and direct applications together
Campus career fairs surface structured internship programs explicitly tied to your university, and professors or career center staff often know which employers recruit from your school before roles post publicly. Apply directly to smaller companies running their own cohorts at the same time, combining both channels reaches programs you'd miss by relying on either one alone.
Practice your technical screen out loud
Ai ml engineering internship interviews typically include a coding screen covering data structures, algorithms, and ML fundamentals, followed by questions where you explain your reasoning on a modeling problem. Practice solving problems while narrating your approach, since interviewers weigh how you think through a problem as much as whether you reach the correct answer.
Target structured ML internship programs early
Many larger technology and research employers run dedicated machine learning or AI internship cohorts designed to train people new to industry. These programs recruit early, fill fast, and offer structured mentorship and project rotations that are harder to replicate in an ad-hoc internship. Identify the programs that match your interests and submit in the first application window.
Set your work-type filter before you start
On-site roles are 100% of the ai ml engineering internships listed here. Decide what you can realistically commit to before you start applying so you're not sorting through roles in cities you can't relocate to or remote positions your program doesn't allow. Filter by location and work type on Migrate Mate to see only the listings that fit your situation.
AI ML Engineering Internships: Frequently Asked Questions
How do I get an ai ml engineering internship?
Lead with coursework and personal projects rather than work history, hiring teams expect limited experience at the intern level. A public GitHub repository with documented ML projects, model experiments, or data pipelines gives recruiters something concrete to assess. Apply directly to companies posting roles and attend campus career fairs, where recruiters often move faster for students they meet in person.
Can an ai ml engineering internship turn into a full-time job?
Many employers extend return offers to strong interns, but conversion is never guaranteed. What drives it for ai ml engineering interns is performance on real project deliverables, team headcount at the end of the summer, and how early return-offer decisions happen at that company. Position for one by owning your project outcomes, but keep applying to full-time roles in parallel so you're not counting on it.
When should I apply for ai ml engineering internships?
Earlier than most candidates expect. Large tech and enterprise employers open summer internship recruiting the preceding fall, sometimes as early as August or September. Smaller companies and co-op programs post much closer to the start date, so openings appear year-round. Checking listings regularly and setting alerts means you won't miss an early window at a program you want.
Are ai ml engineering internships paid?
Most professional ai ml engineering internships in the United States are paid. Compensation varies by company size, industry, and location, larger tech employers and financial services firms typically pay more than startups or nonprofits. Where an employer discloses a range, it appears in the listing, so you can compare before you apply.
What should an ai ml engineering internship resume include?
Lead with two or three complete, documented projects rather than work history. For each project, name the tools and frameworks used, PyTorch, TensorFlow, scikit-learn, SQL, and similar, and link to the code repository or published output so a recruiter can verify the work. Add relevant coursework in machine learning, statistics, or systems. Keep it to one page.
Are there remote ai ml engineering internships?
Yes. Remote and hybrid roles make up 0% of the ai ml engineering internship listings here, with the rest on-site. Remote cohorts fill fast because they attract applicants from every location, so apply early once you find a role that fits. Use the work-type filter to see only remote or hybrid listings without sorting through every posting.
What is an MLOps or research internship in ai ml engineering?
Some larger technology and research organizations run dedicated machine learning research or MLOps internship programs that focus specifically on production model deployment, infrastructure, or foundational research rather than applied product work. These programs target students earlier in their studies, recruit in the fall for the following summer, and are highly competitive, identify the ones aligned with your interests and apply in the first recruiting wave.
Can international students get ai ml engineering internships?
Yes. F-1 students can intern through CPT while enrolled or through OPT work authorization after finishing a degree, and the employer does not have to file anything for either, so many companies are open to international interns. Confirm your eligibility and timing with your university's international student office before accepting an offer.
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