AI/ML Engineer – Vaccine Research
Hybrid (Pearl River, NY area)
We’re partnering with a global biotech organization at the forefront of AI-driven vaccine innovation to build out a high-impact team operating at the intersection of machine learning, immunology, and translational science.
This role sits within a cutting-edge vaccines R&D group applying advanced AI methods to accelerate how vaccines are discovered, designed, and brought to patients. You’ll work closely with scientists, immunologists, and clinical teams to turn complex biological data into meaningful, real-world impact.
What you’ll do
- Build and deploy machine learning models that directly inform vaccine discovery, antigen design, and clinical strategy
- Work across the full lifecycle - from data integration and model development through to real-world application and decision-making
- Apply modern AI approaches (including generative AI and foundation models) to protein engineering and vaccine optimization
- Integrate large-scale, high-dimensional datasets (e.g., omics, immunological, and clinical data) to uncover biological insights
- Partner cross-functionally to translate technical outputs into clear, actionable insights for scientific and leadership teams
- Contribute to publications and stay at the forefront of AI + life sciences innovation
Requirements
- PhD (or MS + industry experience) in a relevant field (ML, computational biology, AI, etc.)
- Strong hands-on experience building and applying machine learning models (not just theoretical exposure)
- Experience working with complex biological or biomedical datasets
- Background in one (or more) of the following:
- Protein engineering / antigen design
- Systems immunology / immune response modeling
- Translational modeling across preclinical → clinical
- Proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow)
- Ability to clearly communicate technical concepts to non-technical stakeholders
Why this role
- Direct impact on next-generation vaccine development
- Work at a unique intersection of AI + immunology + real-world translational science
- Strong emphasis on scientific publication and visibility
- Opportunity to help shape how AI is applied across a broader R&D organization over time
If you're interested in learning more, please send a resume to s.viall@kennedybond.com
