Research Scientist — Agentic AI & Multimodal RL

Simular; Palo Alto (CA); On-site; USD 180,000 - 210,000; Full time

Job summary

Simular is seeking a Research Scientist to push the boundaries of AI research across planning, reinforcement learning, and multimodal reasoning. You will drive end-to-end experiments, from data collection to model evaluation, and collaborate with engineers to bring research prototypes into production.

The role emphasizes publishing results at leading conferences and advancing methods through dataset construction and benchmarking against state-of-the-art models, with a strong focus on real-world

Qualifications

• PhD or equivalent research experience in ML or related field.
• Proven ability to lead and execute a research program from ideation to publication.
• Strong track record of first-author publications in top venues.

Responsibilities

• Shape the future of agentic AI by pioneering new research directions in planning, RL, multimodal reasoning, grounding, human-agent interaction, and alignment.
• Design and execute end-to-end experiments from data collection to model evaluation.
• Develop new methodologies advancing AI agent capabilities for academic and product impact.
• Collaborate with engineers to integrate research prototypes into products.
• Publish and present results at top-tier conferences and contribute to the AI research community.
• Advance hands-on science by designing methods, building datasets, running experiments, and benchmarking against state of the art.

Skills

Planning

Reinforcement learning

Multimodal learning

Computer vision

Representation learning

Experimentation

Publication leadership

Education

PhD in Computer Science or ML

Tools

PyTorch

JAX

Job description

Simular is seeking a Research Scientist to push the boundaries of AI research across planning, reinforcement learning, and multimodal reasoning. You will drive end-to-end experiments, from data collection to model evaluation, and collaborate with engineers to bring research prototypes into production.

The role emphasizes publishing results at leading conferences and advancing methods through dataset construction and benchmarking against state-of-the-art models, with a strong focus on real-world