Work with Python, PyTorch (or JAX/TensorFlow), RL fine-tuning frameworks like TRL or verl, and distributed multi-GPU training. The Reinforcement Learning Team advances RL, Bayesian optimisation, AI agents, LLMs, and vision-language models, applying them to AI for science, chemistry, physics, and robotics while publishing at top venues.

Thomson Reuters★3.9 (4.3k)· London

You'll lead research scientists and engineers developing foundational machine learning capabilities focused on LLM training, data-centric ML, post-training techniques, and evaluation methods using PyTorch, JAX, and TensorFlow. Thomson Reuters Labs conducts advanced ML/NLP research with access to extensive proprietary data, collaborating with academic institutions while publishing findings at top conferences. You'll manage a global team, hands-on coding and experiments, and translate research into deliverables.

Thomson Reuters★3.9 (4.3k)· London

You'll work with PyTorch, JAX, TensorFlow, and cloud infrastructure (AWS, Azure, GCP) on foundational LLM research including continued pretraining, instruction tuning, reinforcement learning alignment, and post-training techniques for reasoning and agent workflows. Thomson Reuters Labs' dedicated ML research division focuses on advancing LLM capabilities through data-centric approaches and novel evaluation methods, collaborating with academic partners and subject matter experts. You'll manage a diverse global team of ML/NLP specialists and engineers conducting cutting-edge research on agent-based AI systems.

Thomson Reuters★3.9 (4.3k)· London

Thomson Reuters Labs seeks a Research Scientist to advance LLM agent research using PyTorch, JAX, or TensorFlow, focusing on agent-based AI systems, post-training techniques, reasoning models, tool use, and evaluation methods. You'll conduct foundational ML research on continued pretraining, instruction tuning, reinforcement learning alignment, and data-centric ML, collaborating with internal teams and academic institutions while publishing findings and developing proprietary models. The role requires a PhD in a relevant discipline and first-author publications at top-tier conferences on agent systems or multi-agent coordination.