Acceler8 Talent
Machine Learning Researcher (Sonoma)
Acceler8 Talent, Sonoma, California, United States, 95476
Research Scientist
Location:
SF Bay Area (On-site)
Were representing a cutting-edge AI organization building autonomous systems that can
reason, plan, and interact with the physical world.
This is a chance to join a small, elite research team pushing the frontier of LLM-driven autonomy.
The Opportunity Youll lead research that powers intelligent agents capable of long-horizon reasoning, structured tool-use, and real-world decision-making. This is deep ML research with immediate, tangible impact.
What Youll Work On Building LLM reasoning and planning frameworks Designing structured tool-use, memory, reflection, and multi-step workflows Developing safe, robust policies for autonomous systems Training and evaluating models across real engineering and scientific tasks Collaborating with systems, simulation, and infrastructure experts
What Were Looking For Strong research background in LLMs, reasoning, or agents Experience with SFT, RLHF/DPO, verifier-guided RL, or related training techniques Ability to design and evaluate long-horizon behaviors Comfort working in a fast, interdisciplinary R&D environment
Why Join Build models that control
real
physical-world systems,
NOT
just simulations Massive scope for autonomy, creativity, and impact Competitive compensation + meaningful ownership
SF Bay Area (On-site)
Were representing a cutting-edge AI organization building autonomous systems that can
reason, plan, and interact with the physical world.
This is a chance to join a small, elite research team pushing the frontier of LLM-driven autonomy.
The Opportunity Youll lead research that powers intelligent agents capable of long-horizon reasoning, structured tool-use, and real-world decision-making. This is deep ML research with immediate, tangible impact.
What Youll Work On Building LLM reasoning and planning frameworks Designing structured tool-use, memory, reflection, and multi-step workflows Developing safe, robust policies for autonomous systems Training and evaluating models across real engineering and scientific tasks Collaborating with systems, simulation, and infrastructure experts
What Were Looking For Strong research background in LLMs, reasoning, or agents Experience with SFT, RLHF/DPO, verifier-guided RL, or related training techniques Ability to design and evaluate long-horizon behaviors Comfort working in a fast, interdisciplinary R&D environment
Why Join Build models that control
real
physical-world systems,
NOT
just simulations Massive scope for autonomy, creativity, and impact Competitive compensation + meaningful ownership