Research Scientist

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.

As a Research Scientist at Simular, you will:

• →

  Shape the future of agentic AI by pioneering new research directions in planning, reinforcement learning, multimodal reasoning, grounding, human-agent. interaction, and alignment (e.g. reward modeling, automated task evaluation, AI safety).

• →

  Design and execute experiments end-to-end: from data collection and benchmarking, to model training and evaluation.

• →

  Develop new methodologies that push the boundaries of AI agent capabilities and reliabilities, advancing both academic and product impacts, in collaboration with world-class scientists and engineers.

• →

  Collaborate closely with engineers to integrate research prototypes into product

• →

  Publish and present results at top-tier conferences, contributing to the broader AI research community.

• →

  Advance the science hands-on through designing methods, building datasets, running experiments, and benchmarking against state of the art.

• PhD in Computer Science, Machine Learning, or related field, or equivalent research experience.

• Experience owning the complete research lifestyle: leading and executing a research program from ideation all the way to publication.

• Expertise in one or more of (but not limited to) the following areas:

  • Pre-training, post-training, or fine-tuning LLMs/VLMs

  • Reinforcement learning and/or LLM-based agents

  • Computer vision and multimodal learning

  • Representation learning and embeddings.

• Consistent publication record as first author in leading conferences (NeurIPS, ICML, CVPR, ACL, etc.).

• Strong implementation skills in modern ML frameworks (PyTorch, JAX, etc.).

• Demonstrated ability to run complex experiments, analyze results, and iterate quickly.

• Passion for high-impact research with real-world applications.

• Ambition and vision to redefine what’s possible in AI research and deployment.