Machine Learning Scientist II/Senior Scientist, Chemistry

COMPANY DESCRIPTION Our start-up is building a novel chemical discovery platform to reshape how we develop formulations at the molecular level. By combining artificial intelligence with a cutting-edge laboratory discovery pipeline, our interdisciplinary team will chart an unexplored chemical landscape, enabling breakthroughs in drug delivery, agrichemical formulation, and safe, high-performance industrial chemicals. Our company is backed by Flagship Pioneering, a biotechnology origination company that has founded and developed over 115 scientific ventures over the past 25 years. Flagship Pioneering is dedicated to the development of an ecosystem of first-in-category life sciences companies, resulting in $20+ billion in aggregate value, 500+ issued patents, and more than 50 clinical trials for novel therapeutic agents. THE ROLE We are seeking a motivated Senior ML Scientist to lead the predictive pipeline of a lab-in-the-loop platform for novel chemistry. You will define and implement models that reason through the physical rules that govern chemistry to predict the properties of physiochemical interactions at the molecular level. The ideal candidate is eager to take the lead on building a chemistry discovery platform from scratch and be the team’s computational visionary. KEY RESPONSIBILITIES Lead the design, development and validation of models that predict phase behaviors and physiochemical properties of chemical mixtures across temperature, hydration, and concentration gradients Architect and own a generative “lab-in-the-loop” modeling pipeline, that incorporates human input of the chemical formulation scientist, integrates experimental feedback and proposes the next set of experimental samples to be tested in the wet lab Build on top of next-generation chemistry ML methods, such as chemical LLMs, reaction prediction, and electronic structure methods like DFT Own the data flow pipeline, including definition of data standards and processing, data distribution analysis, and visualization to guide the team and inform decision-making processes Act as a technical thought partner to chemists, experimental scientists, and leadership, translating scientific questions into modeling strategy and experimental design PROFESSIONAL EXPERIENCE QUALIFICATIONS PhD (or equivalent experience) in machine learning, computational chemistry, organic chemistry, chemical engineering, materials science, or related field 2+ years of demonstrated experience leading or independently driving the development, training, and validation of ML models in chemistry, materials science, or related domains in a postdoc, industry, or other professional setting Knowledge of fundamentals of chemical properties is essential Proficiency in Python-based deep-learning frameworks (e.g. torch, PyTorch lightning), ML logging software (e.g. MLFLow, WandB), relevant scientific libraries for chemistry (e.g. RDKit), and hyper-parameter optimization (e.g. Optuna) Ability to design, maintain, and evolve Python compute environments and ML infrastructure Strong code organization and reproducibility work ethics and usage of git-based workflows Familiarity with cloud/HPC frameworks (e.g. AWS, azure), containerization (e.g. docker), and batch compute Experience handling large, noisy experimental datasets Strong team player: ability to communicate and work hand-in-hand with chemists, lab scientists, and operational team members Experience with DFT and molecular dynamics tools preferred Experience in Bayesian optimization, active learning, reinforcement learning preferred Prior work on lab-in-the-loop platforms or early-stage teams preferred Knowledgeable in thermodynamics, statistical mechanics, and hydrogen-bonding interactions; familiarity with phase-diagram analysis preferred LOCATION: Cambridge, MA ABOUT FLAGSHIP PIONEERING: Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human heal ... (truncated, view full listing at source)