Research Scientist (Autonomous Agents)

TL;DR

Research Scientist (Autonomous Agents): Leading and supporting research in next-generation autonomous agents to assist humans with an accent on fast online adaptation, continual knowledge consolidation, and robust self-improvement methods. Focus on developing novel technical solutions for real-world agent use-cases and designing robust evaluation protocols.

Location: Must be based in London, UK

Company

hirify.global is a team of scientists, engineers, and ML experts advancing the state of the art in artificial intelligence for public benefit and scientific discovery.

What you will do

• Lead/support research agendas aimed at producing practically applicable technological advances in autonomous agents.
• Participate in the ideation and development of new use-cases and desired capabilities of human-oriented agents.
• Partner with research engineers to develop ambitious prototypes and design evaluation protocols.
• Identify roadblocks and research challenges through empirical study, and develop novel technical or methodological solutions.
• Identify sources of data, design and implement data collection processes, and conduct human annotation and evaluation campaigns.
• Help identify methods and teams within hirify.global for collaboration and overcoming challenges.

Requirements

• PhD in a technical field or equivalent practical experience.
• Experience in a research domain connected to autonomous human-oriented agents (e.g., LLM-powered agents, RL/IL, applications in NLP, evaluation design).
• Desire to produce next-generation agentic systems capable of learning and adapting to real-world scenarios.
• Strong technical background in RL, Imitation Learning, Distillation, and working with/designing environments.
• Experience with In-Context Learning and Continual Learning (either in the context of RL or LLM).
• Work onsite in London, UK.

Nice to have

• Strong end-to-end system building and prototyping skills.
• Experience with fine-tuning LLMs, running human data collection/annotation campaigns, self-play, multi-agent systems, meta-learning, meta-RL, and/or skill-discovery.
• Experience with open-ended learning, RL, and frontier methods for training LLMs (RLVR, RLHF, RLAIF, multi-turn RL, multi-agent interactions, reward function design and modelling).
• Curiosity about, or experience with research topics surrounding personalization, memory, reasoning, self-improvement, and safety.
• Experience with designing and evaluating agentic tasks.

Culture & Benefits

• Value diversity of experience, knowledge, backgrounds and perspectives to create extraordinary impact.
• Committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition.
• Accommodation for disabilities or additional needs.