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Ai Phd Intern Jobs (NOW HIRING)

Fujitsu

Agentic AI Research Intern

Santa Clara, CA · On-site

$40 - $50/hr

Agentic AI Research Intern Job Location: Santa Clara, California Location Flexibility: Multiple ... We are seeking a highly motivated PhD intern to work on LLM-based agents for end-to-end software ...

Fujitsu

Agentic AI Research Intern

Santa Clara, CA · On-site

$40 - $50/hr

We are seeking a highly motivated PhD intern to work on LLM-based agents for end-to-end software ... The intern will collaborate with AI researchers and engineers to develop agent systems that can ...

Docugami

Data Science PhD Intern

Kirkland, WA

We're now looking for AI, NLP, Machine Learning, Data Science, and Math PhD Interns to work alongside our world-renowned science and engineering team to create a revolutionary product. We are looking ...

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How much do ai phd intern jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for ai phd intern in the United States is $19.31, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $20.91 per hour, depending on experience, location, and employer.

What does an AI PhD intern do?

As an AI PhD Intern, you can expect to work on cutting-edge research projects that align closely with ongoing initiatives in the company's AI or machine learning teams. Projects often involve developing novel algorithms, conducting experiments, analyzing large datasets, or contributing to the improvement of existing models. Interns typically collaborate with senior researchers, engineers, and other interns, participating in regular team meetings and presenting findings. Responsibilities are structured to provide mentorship while encouraging independent problem-solving, giving you both guidance and autonomy to drive meaningful contributions.

What is an AI PhD intern?

AI PhD interns are doctoral students or candidates specializing in artificial intelligence who temporarily work at companies, research labs, or academic institutions. Their primary role is to apply advanced AI concepts, conduct research, and contribute to innovative projects while gaining real-world experience. These internships often involve designing experiments, developing machine learning models, and publishing findings alongside experienced researchers. The position provides valuable networking opportunities, hands-on learning, and exposure to cutting-edge technologies in the AI field.

What skills and qualifications are needed to thrive as an AI PhD intern?

To thrive as an AI PhD Intern, you need a strong background in machine learning, statistics, and programming, typically supported by ongoing doctoral studies in computer science, AI, or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with data analysis tools, and knowledge of research methodologies are essential. Strong problem-solving abilities, collaboration, and clear communication skills help you work effectively within research teams and present findings. These skills are crucial for contributing meaningful research, advancing projects, and integrating with multidisciplinary teams in a competitive, innovation-driven environment.
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Infographic showing various Ai Phd Intern job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution, with an average salary of $40,174 per year, or $19.3 per hour.

PhD Research Intern

Simular

Palo Alto, CA • On-site

Other

Re-posted 14 days ago

Job description

PhD Intern

Where multiple locations are listed for this role, the position may be based in any of those locations, with priority determined according to the order of listing.

What you'll do

As a PhD intern, you will:

  • Collaborate with research scientists to advance methods in:
    • Planning and RL for computer use (e.g. behavioral cloning, RL on model weights, RAG-based domain knowledge)
    • Multimodal grounding (e.g. vision-only models, tree search, hybrid methods with large models)
    • Reward/judge modeling (e.g. error analysis, human evaluation, training judge models)
    • User intent understanding (e.g. modeling vague queries, preference learning)
  • Contribute to building datasets, running experiments, and benchmarking results
  • Explore novel approaches and help derisk Simular's long-term technical roadmap
  • Document and communicate findings through internal reports or academic-style writing

You might be a fit if

  • Currently pursuing a PhD in Computer Science, Machine Learning, or related field
  • Research background in at least one of: Reinforcement learning, Large language/vision-language models, Computer vision and multimodal perception, Representation learning
  • Experience conducting experiments and publishing or preparing papers in top-tier conferences (NeurIPS, ICLR, ICML, CVPR, ACL, etc.)
  • Strong coding and prototyping skills in Python and ML frameworks (PyTorch/JAX)
  • Curiosity, initiative, and interest in bridging fundamental research with applied AI

Apply