PhD Research 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.

• 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

• 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