--- title: 'Machine Learning Scientist — Large Multimodal Models (Post-Training) at Iambic Therapeutics, Inc' canonical: 'https://feeny.ai/job/machine-learning-scientist-large-multimodal-models-post-training-iambic-7rzbhfe24hz9' type: 'job' last_seen: '2026-09-09' --- # Machine Learning Scientist — Large Multimodal Models (Post-Training) at Iambic Therapeutics, Inc - **Company:** Iambic Therapeutics, Inc - **Location:** United Kingdom - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2026-08-27 - **Last confirmed live:** 2026-09-09 - **Apply:** https://jobs.ashbyhq.com/iambic-therapeutics/1232cf39-832c-494f-99b9-1b4ee7266a42 ## Job description ## 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 strong publication or deployment record. This is a remote position, with the option to be on-site in our Bristol office. ## KEY RESPONSIBILITIES - Research and develop post-training strategies for large-scale multimodal foundation models - Design reward functions, training objectives, data-generation strategies, and evaluation protocols for reinforcement learning and other post-training approaches applied to multimodal LLMs - Build systematic experimentation and hyperparameter optimization workflows to efficiently explore post-training recipes, model configurations, and training strategies - Develop and apply inference optimization techniques to support deployment in both high-throughput model evaluation and interactive discovery workflows - Design and maintain rigorous benchmarking and evaluation frameworks that measure model quality across modalities, downstream tasks, and scientific use cases - Collaborate with ML and software engineering colleagues to productionize models, evaluation systems, and inference services - Partner with computational chemists, medicinal chemists, and biologists to ensure model development and post-training objectives are grounded in drug discovery needs - Communicate results to internal teams, external partners, and at conferences - Write high-quality research and engineering code: refactor, test, document, and package ML components to support team velocity ## QUALIFICATIONS - PhD in machine learning, computer science, computational chemistry, physics, or a related computational STEM field, or equivalent industry experience demonstrating comparable depth - Strong Python and PyTorch skills, including implementing, training, debugging and evaluating deep learning models end-to-end - Demonstrated experience training large-scale transformer models - Demonstrated experience in one or more of the following: - 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 - 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 ## ABOUT IAMBIC THERAPEUTICS Iambic is a clinical-stage life-science and technology company developing novel medicines using its AI-driven discovery and development platform. Based in San Diego and founded in 2020, Iambic has assembled a world-class team that unites pioneering AI experts and experienced drug hunters. The Iambic platform has demonstrated delivery of new drug candidates to human clinical trials with unprecedented speed and across multiple target classes and mechanisms of action. Iambic is advancing a pipeline of potential best-in-class and first-in-class clinical assets, both internally and in partnership, to address urgent unmet patient need. Learn more about the Iambic team, platform, pipeline, and partnerships at iambic.ai http://iambic.ai. ## MISSION & CORE VALUES Our mission is to deliver better medicines through innovations in AI-based discovery technologies. The culture and work at Iambic Therapeutics are profoundly strengthened by the diversity of our people and our differences in background, culture, national origin, religion, sexual orientation, and life experiences. We are committed to building an inclusive environment where a diverse group of talented humans work together to discover therapeutics and create technologies. ## PAY AND BENEFITS We offer a competitive compensation package, private medical insurance, life assurance, pension contributions, and flexible holiday allowances to our team. Our UK office provides a modern and collaborative work environment, right in the centre of Bristol. ## About Iambic Therapeutics, Inc ## Company Overview - **One-liner**: Iambic Therapeutics is a clinical‑stage biotechnology company that uses an AI‑driven platform to discover and develop novel small‑molecule medicines for oncology and other diseases. - **Entity Type**: Private (late‑stage venture‑backed) - **Headquarters**: San Diego, California, United States - **Founded**: 2020 - **Founders**: Not explicitly named in available sources; leadership includes a Co‑Founder & CEO and a Co‑Founder & CTO. ## Core Business - **Primary industries**: Biotechnology, AI‑powered drug discovery, oncology therapeutics - **Target customers**: B2B partnerships with pharmaceutical companies (e.g., Bayer) and, ultimately, patients through a wholly‑owned pipeline of clinical‑stage candidates - **Mission**: *“Better technology for better medicines”* – using machine learning and automation to transform the creation of new therapeutics ## Products & Services - **Enchant Platform**: A multi‑modal transformer AI that breaks down data barriers between preclinical and clinical R&D, enabling rapid molecular design. - **NeuralPLexer**: A co‑folding AI technology that predicts protein‑ligand structures to guide drug design. - **Automated High‑Throughput Experimentation**: AI‑driven robotics that generate new biological data from novel molecular designs on a weekly cadence. - **IAM1363** (HER2 inhibitor): A highly selective, brain‑penetrant tyrosine kinase inhibitor for HER2‑driven cancers; currently in Phase 1b clinical studies. - **IAM‑C1** (CDK2/4 dual inhibitor): A potential first‑in‑class selective inhibitor for HR+/HER2‑ metastatic breast cancer (preclinical). - **IAM‑K1** (KIF18A inhibitor): A potential best‑in‑class allosteric inhibitor for triple‑negative breast cancer, ovarian cancer, and other solid tumors (preclinical). - **Undisclosed programs**: Additional wholly‑owned candidates across multiple target classes and mechanisms. ## Market Standing - **Valuation**: Not publicly disclosed - **Key Metric**: **Total funding** – $330.8 M (including a $100 M Series B in Oct 2023, a $50 M Series B extension in Apr 2024 led by EXOR N.V. and Mubadala Capital, and a $127.8 M venture round in Nov 2025) - **Notable Investors/Partners**: EXOR N.V., Mubadala Capital, Nexus Venture, Bayer (collaboration in AI drug discovery), and a Scientific Advisory Board including Nobel Laureate Frances Arnold (Caltech) - **Growth Signals**: - Headcount of **117** (64.5 % year‑over‑year growth) - Active job postings: **18** (+200 % quarterly, +50 % yearly) - Pipeline advanced from program launch to IND in **2 years** (vs. 6‑year industry average for IAM1363) - Broad platform applicability demonstrated across orthosteric, allosteric, and protein‑protein interaction modalities ## Competitive Advantages - **Speed**: AI‑driven platform can deliver development candidates to clinical trials in roughly one‑third the industry average time. - **Selectivity & Differentiated Profiles**: IAM1363 shows > 5000‑fold selectivity against EGFR, avoiding EGFR‑driven toxicity; IAM‑C1 targets CDK2/4 with a novel selectivity profile. - **Broad Platform Applicability**: Platform has produced leads across diverse protein classes and mechanisms (orthosteric, allosteric, PPI modulators). - **Integration of AI and Drug Hunting**: Tightly integrated team of AI experts and seasoned drug hunters, with a culture of “audacity” that tackles hard chemistry problems. ## Strategic Focus - Advancing the clinical pipeline: IAM1363 Phase 1b, preparing IAM‑C1 and IAM‑K1 for IND‑enabling studies. - Expanding platform partnerships (e.g., Bayer collaboration). - Scaling the organization: actively hiring in ML science, computational chemistry, medicinal chemistry, and clinical operations. - Exploring new therapeutic areas and target classes through the Enchant and NeuralPLexer technologies. ## Why Work Here - **Culture**: Values of **Respect**, **Collaboration**, and **Audacity** – cross‑functional teamwork with resilience and optimism; a flat, high‑trust environment. - **Work Model**: Based in La Jolla/San Diego, CA; the company emphasizes on‑site collaboration for drug‑discovery and lab‑based roles; remote/hybrid policy not explicitly stated. - **Team Growth**: Rapidly scaling (headcount +64 % YoY) with a strong pipeline of open roles in ML, computational chemistry, drug product development, and clinical operations. - **Cutting‑Edge Work**: Opportunity to work at the intersection of frontier AI (large multimodal models, agentic data pipelines) and real‑world drug discovery that reaches patients. - **Leadership & Mentorship**: Advisory board includes Nobel laureate and former NVIDIA AI director; close integration of AI and biology. ## Sources 1. [iambic.ai](https://www.iambic.ai/) – Homepage, platform, and corporate overview 2. [iambic.ai/about](https://www.iambic.ai/about) – Leadership, advisory board, investors 3. [iambic.ai/pipeline](https://www.iambic.ai/pipeline) – Pipeline details (IAM1363, IAM‑C1, IAM‑K1) 4. [iambic.ai/careers](https://www.iambic.ai/careers) – Careers page, values, open positions 5. [linkedin.com/company/iambic-ai](https://www.linkedin.com/company/iambic-ai) – Company stats (headcount 117, $3.4M revenue, $330.8M funding, funding rounds, employee growth) ## Other roles at Iambic Therapeutics, Inc - [Sr Manager, FP&A - Discovery R&D](https://feeny.ai/job/sr-manager-fp-a-discovery-r-d-iambic-therapeutics-inc-san-diego-sznt8xkbx741) — San Diego, CA - [Director/Senior Director, Immunology](https://feeny.ai/job/director-senior-director-immunology-iambic-therapeutics-inc-san-diego-pc8aedpavc67) — San Diego, CA - [Software Engineer — Agentic data pipelines](https://feeny.ai/job/software-engineer-agentic-data-pipelines-iambic-therapeutics-inc-united-states-z1afztyyenvn) — United States - [Principal Medical Writer](https://feeny.ai/job/principal-medical-writer-iambic-therapeutics-inc-united-states-p7p8wv9kdmyd) — United States - [Sr Manager, Quality Systems & Compliance](https://feeny.ai/job/sr-manager-quality-systems-compliance-iambic-therapeutics-inc-united-states-vsh166q5vj7e) — United States - [Research Scientist I/II, Bioanalytical Sciences & Assay Development](https://feeny.ai/job/research-scientist-i-ii-bioanalytical-sciences-assay-development-iambic-z1xnw171hxqv) — San Diego, CA - [Machine Learning Scientist – Clinical Prediction](https://feeny.ai/job/machine-learning-scientist-clinical-prediction-iambic-therapeutics-inc-boston-r8b4amskssr5) — Boston, MA - [Machine Learning Scientist — Large Multimodal Models (Post-Training)](https://feeny.ai/job/machine-learning-scientist-large-multimodal-models-post-training-iambic-tq20zrdrpft4) — Boston, MA - [Senior / Executive Director, Analytical Development CMC](https://feeny.ai/job/senior-executive-director-analytical-development-cmc-iambic-therapeutics-inc-xc2n3pav2s88) — United States - [Associate Director / Director, Clinical Pharmacology](https://feeny.ai/job/associate-director-director-clinical-pharmacology-iambic-therapeutics-inc-san-je8hv9zyhrrm) — San Diego, CA