Machine Learning Scientist — Large Multimodal Models (Post-Training)

The role

You will research and develop post-training methods for Enchant, a multimodal transformer model. You will design and evaluate approaches like supervised fine-tuning and reinforcement learning to advance drug discovery.

What you will do

• Research and develop post-training strategies for large-scale multimodal foundation models
• Design reward functions, training objectives, data-generation strategies, and evaluation protocols
• Build systematic experimentation and hyperparameter optimization workflows
• Develop and apply inference optimization techniques
• Design and maintain rigorous benchmarking and evaluation frameworks
• Collaborate with ML and software engineering colleagues to productionize models
• Partner with computational chemists, medicinal chemists, and biologists
• Communicate results to internal teams, external partners, and at conferences
• Write high-quality research and engineering code

Required qualifications

• PhD in machine learning, computer science, computational chemistry, physics, or a related computational STEM field, or equivalent industry experience
• Strong Python and PyTorch skills
• Demonstrated experience training large-scale transformer models
• Demonstrated experience in supervised fine-tuning, full-parameter fine-tuning, parameter-efficient fine-tuning (LoRA), or related methods
• Demonstrated experience in systematic hyperparameter optimization or large-scale experimentation using tools such as Optuna, Ray Tune, or similar frameworks
• Strong engineering practices: reproducible experimentation, clean code, testing, and performance-aware debugging
• Comfort with modern ML infrastructure (e.g., Docker, CUDA, Kubernetes, experiment tracking tools such as Weights & Biases)

Nice to have

• Reinforcement learning approaches such as RLHF, RLAIF, PPO, GRPO, RL with verifiable rewards, or related methods
• Experience with multimodal or multi-task model architectures
• Training and inference optimization (e.g., mixed precision, kernel optimization, quantization, distributed strategies)
• Familiarity with biomedical, chemical, or biological data domains
• Distributed training at scale
• HPC or large-scale training operations experience

Benefits

• Competitive compensation package
• Private medical insurance
• Life assurance
• Pension contributions
• Flexible holiday allowances

About the company

Iambic Therapeutics is a technology and clinical-stage life sciences company. Their platform integrates proprietary AI with automated, scalable chemistry and biology experimentation to address drug discovery and development.