Physical Intelligence Internship 2027–2028: Programs, Deadlines & How to Apply

Last updated: July 2026

Physical Intelligence has raised over $1 billion at an estimated $11 billion valuation with only about 191 employees, making it one of the highest-valued robotics AI companies per headcount in history. Co-founded in 2024 by Sergey Levine, Chelsea Finn, and Karol Hausman, three of the most cited researchers in robot learning, PI develops foundation models that teach robots to learn any task. For the 2027–2028 cycle, intern postings are expected between October and December 2026. With an estimated cohort of just 5 to 15 interns and an acceptance rate under 5%, applying the week a role appears is the only timing strategy that matters.

Quick Facts

PI is a 191-person, $11B-valued robotics AI startup that hires an estimated 5 to 15 interns per cycle, putting the acceptance rate below 5%. Rolling review and a tiny cohort mean applying the day a posting goes live is the single highest-leverage move.

Externships are short, remote projects where you finish real work for a real company. The Wayfair AI Agent Engineering Externship and Beats by Dre Data Analytics Externship build the Python, ML infrastructure, and systems-thinking evidence a Physical Intelligence application rewards. Explore all Externships.

What Is a Physical Intelligence Internship?

A Physical Intelligence internship is a research-focused placement at a 191-person startup building foundation models that teach robots to perform any physical task. Unlike structured rotational programs at large tech companies, PI embeds interns directly into small research teams working on the pi-0 model family, reinforcement learning, imitation learning, and sim-to-real transfer. The company was founded in 2024 by seven co-founders from Stanford, UC Berkeley, Google Brain, and Stripe, and has shipped three generations of robot foundation models in two years. Interns work in-office in San Francisco alongside researchers whose papers define the field, with the potential for co-authorship on publications at venues like NeurIPS, CoRL, and ICRA. The combination of an $11 billion valuation, a team small enough that every person matters, and a research agenda at the frontier of embodied AI makes PI one of the highest-signal internships in robotics.

When Do Physical Intelligence Internship Applications Open for 2027–2028?

Physical Intelligence does not publish a fixed internship calendar, so the timeline below is projected from industry norms and the company's rapid scaling trajectory. PI grew from roughly 28 employees in early 2025 to about 191 by mid-2026, a sevenfold increase in eighteen months, and intern postings have historically appeared on the Ashby ATS and BuiltIn alongside full-time roles. For the Summer 2027 cycle, expect postings between October and December 2026, rolling interviews through March 2027, and offers by April. The critical insight: with only an estimated 5 to 15 intern seats per cycle, slots fill fast under rolling review. Set alerts on both the Ashby board and pi.website/join-us, and submit the week a relevant posting goes live.

Why You Must Apply the Week Applications Open

Rolling review at a 191-person company with an estimated 5 to 15 intern seats means timing is the sharpest lever you have. PI does not publish fixed deadlines; positions are posted when research teams identify needs, reviewed as they arrive, and filled as soon as a strong candidate clears the loop. Community signals from r/mechatronics confirm that PI is recognized as one of the very few top-tier robotics AI internship destinations, alongside only NVIDIA and Tesla, which compresses the talent pool and accelerates fills. Submitting within days of a posting going live, rather than weeks, is the difference between a full review and a closed requisition. Set alerts on the Ashby ATS and pi.website/join-us, and have your resume, publications list, and research statement ready to go before October 2026.

Which Physical Intelligence Internship Programs Should You Target?

Physical Intelligence does not run a formal multi-track internship program with a glossy landing page. Instead, intern roles appear on the Ashby ATS alongside full-time positions, and each maps to a specific research or engineering team. Two tracks are confirmed from public listings; three more are derived from active full-time openings and are likely to spawn intern equivalents as the company scales.

See every open role on the Ashby job board or pi.website/join-us. PI also accepts open applications: if no exact role matches your background, you can apply under a custom job category. The Robot Operator track is the most accessible entry point, requiring robotics familiarity rather than an advanced degree or publications.

What Are the Eligibility Requirements?

Physical Intelligence's requirements vary by track, but a few patterns repeat across research and engineering roles:

• Degree level: PhD strongly preferred for research internships. MS accepted for applied research, ML infra, and robotics SWE tracks. Robot Operator roles are more accessible and do not require an advanced degree.

• Fields: Computer Science, Electrical Engineering, Mechanical Engineering, Robotics, or a closely related discipline.

• Technical stack: Python required across all tracks. JAX is PI's preferred ML framework (the stack is JAX-first for TPU training), though PyTorch is accepted. Experience with reinforcement learning, foundation models, and hands-on robotics is highly valued.

• Publications: Expected for research track candidates. Top venues include NeurIPS, ICML, ICLR, CoRL, RSS, ICRA, IROS, and CVPR.

• Location: All positions are in-office in San Francisco (Mission District, 94110). No remote internship options. Visa sponsorship is likely available but not explicitly confirmed.

Do I Need a PhD to Intern at Physical Intelligence?

For the Research Intern track, a PhD is practically required. Reddit consensus in r/MachineLearning confirms that a PhD gives significantly more impact and salary at companies like PI, and the founding team's academic pedigree (Berkeley, Stanford, Google Brain) sets a research-first culture bar. However, the MS-accessible tracks (Applied Researcher, ML Infra, Robotics SWE) and the Robot Operator pipeline offer realistic entry points without a doctoral degree. Hands-on experience with real robot hardware, not just simulation, is a strong differentiator regardless of degree level.

What Skills Does Physical Intelligence Look For, and How Do You Build Them?

Read across five PI-related role descriptions, two confirmed intern tracks and three derived from full-time postings, and the pattern is clear. Python appears in all five, JAX or PyTorch in four, reinforcement learning in four, and robot hardware experience in three. But the skill list only tells half the story: PI is building foundation models for the physical world, so the interview will probe whether you can bridge the gap between ML theory and real robot behavior. Sim-to-real transfer experience and hands-on time with physical hardware carry more weight than an extra publication, because PI ships models that move actual arms and legs.

How Is Demand for Robotics AI Interns Moving Right Now?

Build These Skills Before You Apply

And every skill in that chart maps to a remote Externship where you finish a real project before a role opens.

How close is the overlap? The Wayfair project is agent-engineering work that yields the build-and-debug evidence PI's technical interviews probe for, and the Beats project delivers the data-analysis and experiment-design narrative a research presentation needs.

What Is the Physical Intelligence Application and Interview Process Like?

Physical Intelligence does not publish its interview process, but recruiter job descriptions mention structured interviewer calibration, and the loop for comparable robotics AI research roles follows a predictable pattern:

1. Apply on the Ashby ATS or pi.website/join-us. Upload your resume, publications list, and research statement. If no exact role matches, apply under a custom job category. Also check BuiltIn for additional listings.

2. Recruiter screen (30 minutes). Background review, motivation, research interests, and logistics. This stage filters for genuine alignment with PI's mission of bringing general-purpose AI into the physical world.

3. Technical phone screen (45 to 60 minutes). ML and robotics fundamentals, live coding in Python, and discussion of your research area. Expect questions on reinforcement learning, foundation models, and robot learning from demonstrations.

4. Research presentation or deep dive (60 minutes). Present your past research, discuss PI-relevant problems, and demonstrate your ability to think across the theory-to-hardware gap. This round carries heavy weight at research-first companies.

5. Onsite or virtual panel (3 to 5 hours). Multiple rounds covering ML theory and implementation, robotics fundamentals (control, perception, planning), Python and JAX coding, research vision, and team fit. Expect interviewers from the founding team or senior researchers.

The two skills to drill are clear: deep ML fluency for the technical rounds (reinforcement learning, transformer architectures, diffusion models) and a compelling research narrative for the presentation round. PI's founding team includes three of the most cited researchers in robot learning, so your presentation will be evaluated by people who wrote the papers you studied. Prepare accordingly. And note: the Robot Operator track likely has a shorter, more practically oriented loop focused on hands-on robotics aptitude rather than research depth.

What Students on Reddit Say

Four community threads show the landscape from the outside, all paraphrased.

How Do You Stand Out When the Cohort Is 5 to 15 People?

Three moves, all before a posting appears. First, build a research artifact that touches real hardware: PI works with physical robots, not just simulations, so a project that includes sim-to-real transfer or manipulation data collection is worth more than a purely theoretical paper. Second, learn JAX: PI's stack is JAX-first for TPU training, and most candidates default to PyTorch, so JAX fluency is a genuine differentiator. Third, prepare a 20-minute research talk that connects your work to PI's mission of general-purpose physical AI, because the research presentation round is where comparable companies make or break candidates. And remember: PI's co-founders are Sergey Levine, Chelsea Finn, and Karol Hausman. If you have read their papers, cite them in your application, and come ready to discuss the open problems their work surfaces.

What Other Companies Should You Consider?

Physical Intelligence competes for the same robotics-meets-ML talent pool as a handful of other companies. If you are building a research-internship list, these are the obvious neighbors:

Our tech internships summer 2027 guide maps the whole landscape, timeline by timeline.

FAQ

Does Physical Intelligence offer internships?

Yes. PI lists Research Internships on BuiltIn and Robot Operator roles that serve as entry-level pipeline positions on its Ashby ATS. No formal structured internship program page exists; internships are research-focused positions listed alongside full-time roles. Intern cohorts are estimated at 5 to 15 per cycle.

Do I need a PhD to intern at Physical Intelligence?

A PhD is strongly preferred for research internship roles, and community consensus suggests it is practically required for research positions at companies building robot foundation models. However, MS students may qualify for applied research, ML infra, and robotics SWE tracks. Robot Operator roles are the most accessible, requiring robotics familiarity rather than an advanced degree.

How much does a Physical Intelligence internship pay?

No verified PI-specific intern compensation data exists publicly. Based on comparable San Francisco robotics AI startups, estimated compensation is $8,000 to $12,000 per month for PhD research interns and $5,000 to $7,000 per month for MS candidates. Robot Operator roles pay approximately $25 per hour.

Is the Physical Intelligence internship remote?

No. All positions are in-office at PI's San Francisco headquarters in the Mission District (94110). No remote internship options are listed.

What programming language does Physical Intelligence use?

Python is required across all tracks. JAX is PI's preferred ML framework, and the stack is JAX-first for TPU training. PyTorch is accepted as an alternative. For robotics SWE roles, C++ experience is also valued.

When do Physical Intelligence internship applications open for summer 2027?

Postings are expected between October and December 2026, with rolling review through January to February 2027. PI does not publish fixed deadlines. Set alerts on the Ashby ATS and pi.website/join-us and apply the day a relevant role appears.

What is the acceptance rate for Physical Intelligence internships?

Estimated below 5% for research internships, comparable to top AI labs like DeepMind, FAIR, and OpenAI. PI has about 191 employees and is explicitly looking to add a small number of people, with an estimated intern cohort of just 5 to 15 per cycle.

Does Physical Intelligence sponsor visas for interns?

Visa sponsorship is likely available for qualified candidates based on indirect evidence (comparable companies, Jooble listings), but it is not explicitly confirmed on PI's website. CPT is the standard mechanism for F-1 students. Candidates should verify sponsorship during the application process.

Physical Intelligence fills an estimated 5 to 15 intern seats per cycle, but every one of them goes to someone who showed up with research artifacts and real-hardware experience. Spend the runway building proof: a remote Externship turns an interest in robotics AI into a finished project you can point at when the Ashby posting goes live.