- Location
- Palo Alto, California, United States
- Employment
- Internship
- Level
- Internship
- Posted
- 11 months ago
About this role
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
As published by Simular. Applications are handled on their site.
Skills this posting mentions
About Simular
Simular is a research-driven AI company building autonomous computers to free human work and enhance life. Our first product is Sai, an always-on AI agent that uses computers just like humans do. Founded by former AI researchers at Google DeepMind, Simular develops computer-using agents (CUA) that operate across digital environments with human-level capabilities, backed by our benchmark-topping agentic framework. Simular is backed by investors including Felicis, NVentures (Nvidia), South Park Commons, and Lenny Rachitsky.
All 22 openings at SimularOne click, then it is written
Apply to Simular with a resume written for this role.
Queue PhD Research Intern and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Simular’s form for you.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- 25 sent a week, free
- No card
- Nothing sent until you say so
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Put this to work
Paste your career in once. Every application after that is written for you.
Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- New matches ranked and written before you are up.
- Every bullet stays inside what your history supports. Nothing invented.
- Queued, submitted, interviewing, offer: one screen, not a spreadsheet.
500 free credits on sign-up. No card. Nothing is sent until you say so.
Listed from the job board Simular publishes. Refolk is not the employer and does not handle their hiring. Applications go to Simular directly.