Director, AI Model R&D & Training (Hybrid)

Thomson Reuters Corp.; Zug; Hybrid; CHF 180,000 - 260,000; Full time

Benefits offered by this job

Hybrid Work Model

Flex My Way

Career Development

Job summary

Thomson Reuters Labs is seeking a Director of Model Research & Development to lead hands-on post-training for LLMs, including supervised fine-tuning, preference optimization, and reinforcement learning. You’ll design data selection, mixtures, synthetic data, and evaluation, while working with infra and evaluation teams to keep pipelines reliable.

You will oversee a technical team, drive experiments, publish findings, and align ML efforts with product roadmaps for regulated professional workflows.

Qualifications

• Post-training and reinforcement learning depth with hands-on experience.
• Data-centric model development and ability to show impact of data changes.
• Engineering depth in distributed training, data pipelines, and evaluation infra.
• Track record of shipped models, open-source contributions, or top-tier publications.
• Proven technical leadership leading a focused team.

Responsibilities

• Own post-training for Thomson's LLMs: supervised fine-tuning, preference optimization, RL.
• Stand up agentic RL pipelines with domain experts in the loop.
• Own data selection, mixture design, synthetic data generation, and evaluation design.
• Collaborate with infra and evaluation teams to keep training pipelines reliable.
• Inform roadmap and prioritization with findings and recommendations.

Skills

Post-training RL depth

Data-centric model development

Engineering depth

Track record of shipped models/open‑s­

Technical leadership

Tools

Distributed training

Data pipelines

Evaluation infrastructure

Job description

Thomson Reuters Labs is seeking a Director of Model Research & Development to lead hands-on post-training for LLMs, including supervised fine-tuning, preference optimization, and reinforcement learning. You’ll design data selection, mixtures, synthetic data, and evaluation, while working with infra and evaluation teams to keep pipelines reliable.

You will oversee a technical team, drive experiments, publish findings, and align ML efforts with product roadmaps for regulated professional workflows.