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Ai Residency Program Jobs (NOW HIRING)

1X Technologies AS

AI Residency

San Carlos, CA · On-site

$10K/mo

About the Program The AI Residency is a fixed-term position (3-6 months) for researchers and engineers who want to work on high-impact AI and robotics problems alongside full-time 1X team members.

RoboForce

AI Resident

Milpitas, CA · On-site

$10K/mo

The AI Residency Program The AI Residency Program is designed for exceptional early-career researchers and engineers who want to tackle some of the hardest problems in robotics and AI. Residents will ...

RoboForce

AI Resident

Milpitas, CA · On-site

$10K/mo

The AI Residency Program The AI Residency Program is designed for exceptional early-career researchers and engineers who want to tackle some of the hardest problems in robotics and AI. Residents will ...

RadixArk

AI Infra Resident (1-Year Program)

Palo Alto, CA · On-site

$116K - $148K/yr

About The Role RadixArk is launching a full-time, paid, 1-year residency program for aspiring AI infrastructure engineers. You'll rotate across inference, training, kernels, compilers, and cluster ...

RadixArk

AI Infra Resident (1-Year Program)

Palo Alto, CA

$116K - $148K/yr

About The Role RadixArk is launching a full-time, paid, 1-year residency program for aspiring AI infrastructure engineers. You'll rotate across inference, training, kernels, compilers, and cluster ...

RadixArk

AI Infra Resident (1-Year Program)

Palo Alto, CA · On-site

$116K - $148K/yr

RadixArk is launching a full-time, paid, 1-year residency program for aspiring AI infrastructure engineers. The role involves rotating across various aspects of AI infrastructure, working on real ...

RadixArk

AI Infra Resident (1-Year Program)

Palo Alto, CA · On-site

$116K - $148K/yr

RadixArk is launching a full-time, paid, 1-year residency program for aspiring AI infrastructure engineers. The role involves rotating across various domains such as inference and training, working ...

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Ai Residency Program information

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$90.6K

$117.5K

How much do ai residency program jobs pay per year?

As of Aug 2, 2026, the average yearly pay for ai residency program in the United States is $90,556.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,500.00 and $116,500.00 per year, depending on experience, location, and employer.

What is an AI Residency Program?

An AI Residency Program is a structured, typically year-long opportunity designed for individuals interested in gaining hands-on experience and mentorship in artificial intelligence research and development. These programs are often hosted by tech companies or research institutions and pair residents with leading AI researchers to work on cutting-edge projects. Residents participate in seminars, collaborate on publications, and often contribute to real-world AI applications. The goal is to bridge the gap between academia and industry, providing residents with the practical skills and knowledge needed for a career in AI.

What are the key skills and qualifications needed to thrive as an AI Residency Program participant, and why are they important?

To excel in an AI Residency Program, you typically need a strong background in computer science, mathematics, and machine learning, often demonstrated by an advanced degree or relevant research experience. Proficiency with programming languages such as Python, deep learning frameworks like TensorFlow or PyTorch, and experience with data analysis tools are commonly required. Strong problem-solving abilities, curiosity, and effective communication skills help residents contribute to collaborative research and complex projects. These qualifications are crucial for driving innovation, conducting impactful research, and successfully transitioning to advanced AI roles.

What types of projects do participants typically work on during an AI Residency Program?

AI Residency Programs usually immerse participants in real-world, cutting-edge machine learning and artificial intelligence projects, often in collaboration with experienced researchers and engineers. Projects may include developing novel algorithms, improving existing models, or applying AI techniques to solve industry-specific problems such as natural language processing, computer vision, or robotics. Residents often work in small teams, participate in regular research meetings, and are encouraged to publish their results or contribute to open-source initiatives. This hands-on experience not only sharpens technical skills but also provides valuable exposure to collaborative research environments.
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Ai Residency Program jobs near you
Infographic showing various Ai Residency Program job openings in the United States as of July 2026, with employment types broken down into 73% Full Time, 24% Part Time, and 3% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution, with an average salary of $90,556 per year, or $43.5 per hour.

AI Residency Program, Material Science (2026 Cohort)

Lila Sciences

Cambridge, MA • On-site, Remote

Other

Re-posted 6 days ago

Job description

AI Resident - 2026 Cohort

The AI Residency Program is a full-time research opportunity designed to bridge the gap between academic research and industry applications in AI for materials science. Residents will work closely with Lila scientists and engineers on high-impact, open-science projects, with the option to focus on either fundamental or applied research.

  • Duration: 6-12 months (extension possible)
  • Start Dates: First hires beginning January 2026, with rolling applications and additional intakes in Summer and Fall 2026
  • Cohort Size: Small group of selected residents
  • Mentorship: Pairing with technical mentors, feedback from cross-functional teams
  • Resources: Access to proprietary datasets, high-performance compute, and Lila's research infrastructure

Research areas include ML-accelerated simulations, Bayesian methods, representation learning, generative models, agentic science, and ML-driven automation.

 
Application Requirement:
Please submit your resume alongside a research proposal (up to 3 pages, unlimited references) outlining the project you would plan to pursue during your residency at Lila Sciences. Please submit your research proposal as your cover letter. Applications without both documents will not be considered. Optional supporting materials (e.g., recommendation letters, publications, research artifacts) may also be included. 

Your Impact at Lila

The Lila Sciences AI Residency is a full-time research program at the intersection of artificial intelligence and materials science. As a resident, you'll join a cohort of researchers tackling open-ended scientific challenges alongside Lila's world-class team of scientists and engineers. With access to proprietary datasets, high-performance compute infrastructure, and experienced mentors, you'll pursue ambitious research projects with both academic and real-world impact. Publishing is encouraged but not required - what matters most is pushing the frontier of scientific discovery.

What You'll Be Building

  • Design and execute independent research projects in AI for materials science
  • Collaborate with Lila scientists and engineers on cutting-edge, open-science initiatives
  • Explore domains such as ML-accelerated simulations, Bayesian methods, representation learning, generative AI, agentic science, and ML-driven automation
  • Contribute to collaborative team research and co-develop novel approaches to scientific discovery
  • Share findings internally and externally; publications are welcome but not mandatory

What You'll Need to Succeed

  • Degree in Materials Science, Chemistry, Computer Science, AI/ML, Physics, Mathematics, or related field (Bachelor's, Master's, or PhD)
  • Proficiency in Python and deep learning frameworks (e.g., PyTorch)
  • Experience working with large-scale datasets or simulations
  • Familiarity with modern AI/ML architectures and training techniques
  • Strong research background, demonstrated through publications, thesis work, or open-source projects

Bonus Points For

  • Prior work on ML applications in scientific domains (e.g., materials discovery, chemistry, simulations)
  • Familiarity with Bayesian optimization, active learning, or generative models
  • Experience in reinforcement learning or agent-based approaches to scientific reasoning
  • Open-source contributions or collaborative research experience
  • Strong communication and writing skills, especially for conveying complex scientific ideas

Apply