Principal Scientist, Machine Learning

Flagship Pioneering, Inc. • Boston, MA

7h • $212,000 - $291,000

About The Position

We are seeking a Machine Learning scientist to join our computational team to bring SOTA ML models that drive the design and optimization of SynteinsTM. You will work at the interface of peptide science, cheminformatics, and AI, collaborating with experimentalists to optimize molecules for affinity, stability, solubility, and other critical developability properties.
This is a highly interdisciplinary, hands-on role in a fast-moving team. Ideal candidates will have prior experience building or applying ML models to molecular property prediction and optimization in the context of peptides, proteins, or small molecules.

Requirements

• PhD in computational biology, bioengineering, machine learning, or a related field.
• 5+ years of industry experience applying ML to protein, peptide, or small molecule modeling.
• Demonstrated experience building models to predict molecular or physicochemical properties (e.g., solubility, stability, binding).
• Proficiency in Python and ML frameworks (e.g., PyTorch, scikit-learn, RDKit, PyG).
• Experience in diverse deep learning architectures (e.g., GNN, RL, VAE, Transformers, GAN)
• Excellent communication skills with the ability to synthesize AI/ML tools and concepts to team members across many departments

Nice To Haves

• Familiarity with peptide/protein design concepts (e.g., structure-based optimization, binding site modeling, non-canonical amino acids).
• Experience in the application of ML tools in drug discovery
• Experience with experimental collaboration and designing hypotheses that inform synthesis or screening.
• Experience working in a startup, platform company, or cross-functional discovery team.

Responsibilities

• Develop predictive and generative models to guide Syntein optimization for synthesis efficiency, target binding affinity and selectivity, solubility, thermal stability, and protease resistance.
• Integrate large experimental datasets (e.g., mass, purity, yield, binding, inhibition, activity, structure and stability) to train and refine models in a closed-loop system.
• Collaborate with chemists, biologists, and protein designers to design and prioritize Syntein libraries for synthesis and screening.
• Contribute to internal ML pipelines, data infrastructure, and model validation best practices, supporting the scale-up of our discovery platform.

Benefits

• Work on a first-in-class therapeutic modality with unprecedented design flexibility.
• Be part of a fast-moving, data-rich platform with real-time feedback from automated synthesis and screening.
• Collaborate with world-class scientists across the Flagship Pioneering ecosystem.
• Help build the future of programmable biologics.
• healthcare coverage
• annual incentive program
• retirement benefits
• a broad range of other benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: Ph.D. or professional degree