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Ai Residency Jobs (NOW HIRING)

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 ...

Clerk AI

Customer Support Engineer

San Francisco, CA · Hybrid

We're Silicon Valley-based entrepreneurs who have sold companies, gone through the exclusive HF0 AI residency, having previously built teams at Lucasfilms, Samsung, Netflix, DocuSign, and Series B ...

Clerk AI

Product Marketer

San Francisco, CA

$120K - $180K/yr

We're Silicon Valley-based entrepreneurs who have sold companies, gone through the exclusive HF0 AI residency, having previously built teams at Lucasfilm, Samsung, Netflix, DocuSign, and Series B ...

Clerk AI

Vibe Marketer

San Francisco, CA

$140K - $180K/yr

We're Silicon Valley-based entrepreneurs who have sold companies, gone through the exclusive HF0 AI residency, having previously built teams at Lucasfilm, Samsung, Netflix, DocuSign, and Series B ...

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How much do ai residency jobs pay per year?

As of Jul 14, 2026, the average yearly pay for ai residency in the United States is $96,670.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,000.00 and $111,500.00 per year, depending on experience, location, and employer.

Which 3 jobs will survive AI?

AI residency programs prepare individuals for roles that require advanced technical skills, such as AI research scientist, machine learning engineer, and data scientist. These jobs involve complex problem-solving, creativity, and domain expertise that are less susceptible to automation. Continuous learning and proficiency with AI tools and programming languages like Python are essential for these roles.

What is an AI residency program?

An AI residency program is a structured, typically year-long training initiative designed to help individuals gain hands-on experience in artificial intelligence research and development. Residents work closely with mentors at leading research institutions or technology companies, contributing to real-world projects in areas like machine learning, computer vision, or natural language processing. These programs are aimed at early-career researchers, recent graduates, or professionals transitioning into AI, providing mentorship, access to resources, and opportunities to publish or present research. The goal is to bridge the gap between academic learning and professional AI research roles.

What is an AI resident job?

An AI resident job is a position designed for individuals to gain hands-on experience in artificial intelligence research and development. These roles often involve working with machine learning models, data analysis, and programming tools like Python or TensorFlow, typically within a structured training or mentorship program. AI residencies aim to develop skills in AI techniques and contribute to real-world projects under supervision.

What is the difference between Ai Residency vs Data Scientist?

AspectAi ResidencyData Scientist
Required CredentialsTypically a master's or PhD in AI, Machine Learning, or related fieldsOften a bachelor's or master's in Data Science, Statistics, or Computer Science
Work EnvironmentResearch-focused, often in tech companies or research labsBusiness-oriented, working with data analysis and modeling in various industries
Employer & Industry UsagePrimarily in tech giants, research institutions, startupsAcross finance, healthcare, tech, retail, and more

Ai Residency programs are research-focused roles designed to develop AI expertise, often in a structured, immersive environment. Data Scientists work on analyzing data, building models, and deriving insights for business decisions. While both roles require strong technical skills, Ai Residencies emphasize research and innovation, whereas Data Scientists focus on applied data analysis in diverse industries.

What is the highest paid AI career?

The highest paid AI careers typically include roles such as AI research scientists, machine learning engineers, and AI directors, with senior positions often earning six-figure salaries or higher. These roles require advanced skills in deep learning, data science, and experience with tools like TensorFlow or PyTorch, often combined with a strong educational background in computer science or related fields.

What are some common challenges faced by AI residents during their residency programs?

AI residents often encounter the challenge of balancing rigorous research with practical application, as they are expected to contribute to ongoing projects while also pursuing independent research. The fast-paced nature of advancements in AI means residents must continuously stay up-to-date with the latest techniques and literature. Additionally, collaborating effectively with cross-disciplinary teams—such as software engineers, data scientists, and domain experts—can be demanding but is essential for impactful outcomes. Time management and adapting to evolving project goals are also key skills that residents typically develop during their program.

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

To thrive as an AI Resident, you need a strong background in computer science, mathematics, and machine learning, often supported by an advanced degree (Master’s or PhD) in a relevant field. Experience with programming languages like Python, deep learning frameworks such as TensorFlow or PyTorch, and familiarity with research tools are typically expected. Strong problem-solving abilities, collaboration, and effective communication help you contribute to innovative research and work well within interdisciplinary teams. These skills are crucial for advancing AI research, building novel solutions, and driving impactful results in a highly competitive environment.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior researcher, machine learning director, or AI executive, often requiring advanced skills in deep learning, data science, and programming. These roles usually involve leadership, strategic planning, and extensive experience, and they may be found in large tech companies or specialized AI firms. Compensation at this level reflects significant expertise and responsibility in developing and deploying AI solutions.
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Ai Residency jobs near you
Infographic showing various Ai Residency job openings in the United States as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $96,670 per year, or $46.5 per hour.

AI Residency Program, Material Science (2026 Cohort)

Lila Sciences

Cambridge, MA • On-site, Remote

Other

Re-posted 17 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