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Iambic Therapeutics is seeking a Machine Learning Scientist to join the Enchant team, working on post-training methods for large multimodal transformer models applied to drug discovery. The role focuses on researching and developing post-training approaches including supervised fine-tuning, parameter-efficient fine-tuning (LoRA), reinforcement learning (RLHF, RLAIF, PPO, GRPO), and reward-based optimization for biomedical foundation models.
Key responsibilities include designing and evaluating post-training strategies for multimodal LLMs, creating reward functions and training objectives, building systematic experimentation and hyperparameter optimization workflows, developing inference optimization techniques, designing rigorous benchmarking frameworks, and collaborating with ML engineers and domain scientists (computational chemists, medicinal chemists, biologists) to ground model development in real drug discovery needs. You will also productionize models and evaluation systems, communicate results internally and at conferences, and maintain high-quality, well-tested research and engineering code.
Required qualifications: PhD in machine learning, computer science, computational chemistry, physics, or related computational STEM field (or equivalent industry experience); strong Python and PyTorch skills with end-to-end deep learning model implementation and debugging; demonstrated experience training large-scale transformer models; and hands-on experience in reinforcement learning methods (strongly preferred), supervised/parameter-efficient fine-tuning, systematic hyperparameter optimization, or modern ML infrastructure (Docker, CUDA, Kubernetes, Weights & Biases).
Preferred: multimodal or multi-task model architecture experience, training and inference optimization techniques (mixed precision, quantization, distributed strategies), familiarity with biomedical/chemical/biological data domains, distributed training at scale, and HPC or large-scale training operations experience.
Iambic is a clinical-stage biotech company founded in 2020, based in San Diego, developing novel medicines using an AI-driven discovery platform. The company has demonstrated rapid delivery of drug candidates to human clinical trials across multiple target classes. The role is remote with optional on-site presence in the Boston office.
