Director, LLM Research & Development (Hybrid)

Reuters; Zug; Hybrid; CHF 250,000 - 380,000; Full time

Benefits offered by this job

Hybrid Work Model

Flex My Way

Career Development and Growth

Industry Competitive Benefits

Culture and Inclusion

Social Impact & ESG initiatives

Job summary

Thomson Reuters Labs seeks a Director of Model Research & Development to steer the hands-on technical direction of the AI research program in a hybrid setup across Switzerland and the UK. You will oversee post-training, data strategy, experiments, and collaboration with infra and eval teams to ship trusted professional AI systems.

The role emphasizes building robust pipelines, evaluating models, and guiding a team of researchers and engineers toward practical, regulated deployments in legal,

Qualifications

• Post-training and reinforcement learning depth demonstrated in practice.
• Shaped data selection, mixture design, synthetic data generation, and evaluation design with measurable impact.
• Experience building and debugging distributed training and evaluation pipelines.

Responsibilities

• Own hands-on post-training for Thomson's LLMs: supervised fine-tuning, preference optimization, RL in agentic settings.
• Lead data selection, synthetic data generation, and evaluation design; track changes and effects.
• Collaborate with infra and evaluation teams to keep pipelines reliable and scalable.
• Present findings to influence roadmap and priorities.

Skills

Post-trainingRL depth

Data-centric development

Engineering depth

Research leadership

Team leadership

Education

PhD in CS/ML or related

Tools

Distributed training

Data pipelines

Evaluation infrastructure

Job description

Thomson Reuters Labs seeks a Director of Model Research & Development to steer the hands-on technical direction of the AI research program in a hybrid setup across Switzerland and the UK. You will oversee post-training, data strategy, experiments, and collaboration with infra and eval teams to ship trusted professional AI systems.

The role emphasizes building robust pipelines, evaluating models, and guiding a team of researchers and engineers toward practical, regulated deployments in legal,