AI ML Engineer Internships
Ai ml engineer internships give university students, recent graduates, and early-career switchers hands-on project experience building and deploying real models, mentorship from working engineers and scientists, and, at many employers, a path toward a full-time offer. Roles cover Food & Beverage, 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 Engineer Internship Market
Who's Hiring
Top Industries Hiring
- Food & Beverage
Tips for Your AI ML Engineer Internship Search
Apply in the fall for summer roles
Large tech companies, research labs, and financial-sector employers open ai ml engineer intern recruiting in September and October for the following summer. Waiting until spring means competing for a much smaller pool of remaining spots. Smaller companies and co-ops post closer to start dates, so check consistently throughout the year.
Build a portfolio before you apply
Hiring teams for ai ml engineer interns expect limited work history and look at what you have built instead. Create two or three end-to-end projects, model-training pipelines, or published notebooks that demonstrate your grasp of machine learning concepts and Python. Link everything in your resume and profile so recruiters can assess your skills directly.
Work your campus network and apply directly at the same time
Campus career fairs surface structured internship programs tied to your university, and professors or career center staff often know which employers recruit from your school before roles appear publicly. Apply directly to companies running smaller cohorts at the same time, since many ai ml engineer intern openings never get promoted at campus events.
Practice the technical screen out loud
Ai ml engineer intern interviews typically include a coding screen on data structures, algorithms, and machine learning fundamentals, often followed by a take-home or live model-design problem. Practice solving problems aloud and narrating your reasoning, since interviewers weigh how you approach a problem as much as whether you reach the right answer.
Target structured university and rotational programs early
Large technology, research, and data-science employers run cohort-based ai ml engineer intern programs designed to onboard people new to applied ML in a professional setting. These programs recruit in the fall, fill their first-wave spots quickly, and offer more structured mentorship than ad hoc intern roles. Identify the programs that fit your background and apply before the cohort closes.
Set your work-type filter before you start
On-site roles are 100% of the ai ml engineer internships listed here. Decide what you can realistically commit to, whether that is on-site, hybrid, or remote, before you start searching on Migrate Mate, then filter by location and work type so you are only reviewing roles you can actually accept.
AI ML Engineer Internships: Frequently Asked Questions
How do I get an ai ml engineer internship?
Lead with coursework and personal projects rather than work history, hiring teams expect limited experience at the intern level. The concrete artifact that gives recruiters something to assess is a portfolio of documented ML projects: linked GitHub repositories, notebooks, or deployed demos showing your modeling and coding work. Combine direct applications with campus career fairs, where recruiters often move faster for students they meet in person.
Can an ai ml engineer internship turn into a full-time job?
Many employers extend return offers to strong interns, but conversion is never guaranteed. What actually drives it is consistent performance on real project work, whether the team has open headcount when you finish, and how early you signal interest in returning. Position yourself by delivering on your assigned scope and asking your manager about return-offer timelines, but plan your job search independently so you are not caught without options.
When should I apply for ai ml engineer internships?
Earlier than most students expect. Large tech and research employers open summer intern recruiting the preceding fall, often in September and October, and fill cohorts well before the new year. Smaller companies and co-op programs post closer to their start dates, so openings appear year-round. Check early and apply as soon as a role fits your background rather than waiting for a single application season.
Are ai ml engineer internships paid?
Most professional ai ml engineer internships in the United States are paid. Compensation varies by company size, industry, and location, and listings show it where the employer chooses to disclose it. Academic research internships and some nonprofit programs do run unpaid or stipend-only, so read each listing carefully to confirm the compensation structure before applying.
What should an ai ml engineer internship resume include?
Lead with two or three complete, documented projects rather than work history. For each project, name the tools and frameworks you used and link directly to the code repository, trained model, or published notebook so reviewers can assess your work firsthand. Add relevant coursework in machine learning, statistics, and software engineering. Keep the entire document to one page.
Are there remote ai ml engineer internships?
Yes. Remote and hybrid roles make up 0% of the ai ml engineer internship listings here, with the rest on-site. Remote cohorts fill quickly because they attract candidates nationally, so apply early once you decide remote works for you. Filter by work type to surface those listings and avoid sorting through roles you cannot commit to.
Can international students get ai ml engineer 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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