Associate Director, AI/ML Research Scientist

Associate Director, AI/ML (Biologics)
Boston, MA | Full-time | On-site
Join a research and development team applying artificial intelligence and machine learning to transform large-molecule drug discovery. This role will lead the development and application of advanced computational methods across biologics modalities, including antibodies, bispecifics, antibody-drug conjugates (ADCs) and fusion proteins.
Working across computational science, biology and drug discovery, you’ll shape the AI/ML methodological roadmap, embed computational capabilities into drug programmes, and partner with senior stakeholders to advance therapeutic discovery and development.
Key Responsibilities
Develop and implement advanced AI/ML methods for de novo biologics design and optimisation across antibodies, bispecifics, VHHs/nanobodies and other modalities.
Fine-tune protein language models and apply generative protein design techniques.
Build machine learning models for multi-objective optimisation of antibodies, antigens, ADCs and other biologics.
Develop predictive models for protein design, binding affinity and developability engineering.
Integrate data from Design-Predict-Make-Confirm cycles and automated experimental platforms to support project-specific and foundational models.
Manage large-scale biological datasets from NGS, in vitro, in vivo and other internal and external sources.
Identify opportunities to apply AI/ML across drug discovery programmes and translate scientific questions into tractable modelling problems.
Collaborate with computational scientists, biologists, engineers and drug discovery teams to advance research.
Shape the team’s methodological roadmap and represent AI/ML in discussions with senior stakeholders across Discovery Biology, CMC and programme leadership.
Communicate complex scientific concepts to technical and non-technical audiences, while mentoring and supporting colleagues across functions.
Requirements
PhD in a scientific discipline with 6+ years of relevant experience; alternatively, a Master’s degree with 12+ years or a Bachelor’s degree with 14+ years.
Demonstrated experience developing machine learning models for chemical or biological data, including molecular generation and affinity prediction.
Experience modelling antibody and antigen sequences, structures and interactions.
Strong Python programming skills and experience with cloud computing.
Strong analytical, problem-solving and scientific communication skills.
Ability to work independently while collaborating effectively across multidisciplinary teams.
Strategic thinking, scientific curiosity and the ability to identify opportunities for applying AI/ML to complex discovery challenges.
Preferred Qualifications
Experience with modern ML architectures for antibody design, including LLMs, diffusion models, flow matching, Bayesian optimisation or graph neural networks.
Experience designing de novo binders for specific targets and epitopes.
Experience analysing NGS-derived antibody repertoires for sequence- and structure-based design.
Knowledge of molecular simulation and conformational analysis techniques.
Compensation & Benefits
Base salary: $154,400–$242,550 per year
Comprehensive employee benefits package.
The final salary offer may vary based on experience, qualifications, skills and work location.