Iambic has created a cutting-edge AI-driven platform to tackle the most challenging design problems in drug discovery and address unmet patient need. Backed by Sequoia.
About the role
We are seeking a Machine Learning Scientist to join the Enchant team at Iambic Therapeutics. Our mission is to deliver better medicines through innovation in AI-based discovery technologies. In this role, you will research and develop post-training methods for Enchant - our multimodal transformer model trained on a wide variety of biomedical data - pushing the boundaries of what large-scale foundation models can achieve in drug discovery.
What they're looking for
- Reinforcement learning approaches such as RLHF, RLAIF, PPO, GRPO, RL with verifiable rewards, or related methods (strongly preferred)
- Supervised fine-tuning, full-parameter fine-tuning, parameter-efficient fine-tuning (LoRA), or related methods
- 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)
- PREFERRED
More about this role
JOB SUMMARY
We are seeking a Machine Learning Scientist to join the Enchant team at Iambic Therapeutics. Our mission is to deliver better medicines through innovation in AI-based discovery technologies. In this role, you will research and develop post-training methods for Enchant - our multimodal transformer model trained on a wide variety of biomedical data - pushing the boundaries of what large-scale foundation models can achieve in drug discovery.
The role centers on designing and evaluating post-training approaches for large multimodal language models including supervised fine-tuning, parameter-efficient fine-tuning, reinforcement learning, preference or reward-based optimization, and other emerging post-training methods. You will develop rigorous evaluations and training infrastructure that make it possible to rapidly iterate on these approaches at scale and work closely with colleagues across machine learning, software engineering, and drug discovery to put powerful foundation models into the hands of scientists making real therapeutic decisions.
We are hiring across multiple levels and welcome candidates ranging from recent PhD graduates to experienced researchers with a...
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