AI/ML Engineer

About the RoleOur client, a global life sciences company focused on animal health, is looking for an AI/ML Engineer to help speed up its R&D pipeline. You'll turn proprietary scientific data into predictive models that inform discovery and development decisions. You'll work closely with discovery and development scientists to build machine learning and computer vision models on molecular, in vitro, ADMET and imaging data. These models will support target identification, molecular optimization, digital biomarkers and endpoint prediction. What You'll DoOwn the ML and computer vision work on priority R&D programs. You'll work with scientists to turn questions about targets, molecular optimization, in vitro results, ADMET and biomarkers into well-defined modeling problems with measurable success criteria.Design, train and validate advanced models, including CNNs, transformers, graph neural networks and generative methods. You'll work across multi-modal data (molecular, assay, imaging and behavioral) to produce reliable predictions and classifications.Shape how data is collected and labeled. You'll work with lab teams to define capture protocols, annotation standards and quality checks. You'll also assess synthetic data and augmentation techniques to strengthen sparse datasets while keeping bias and risk under control.Put models to work in day-to-day R&D. You'll build and deploy on Databricks, integrate models into the tools scientists already use, and help set standards for reproducibility, documentation, monitoring and model governance.Act as a technical leader. You'll mentor junior scientists, drive cross-functional modeling initiatives and explain complex technical results clearly to varied audiences. Minimum QualificationsEducation: PhD in a quantitative discipline such as Data Science, Engineering, Physics, Mathematics, Statistics, Bioinformatics or Computational Chemistry. A Master's degree with significant hands-on ML/CV experience will also be considered.Experience: 7+ years in industry building and deploying ML and computer vision models for scientific applications in biomedical, pharmaceutical or adjacent fields. You'll need demonstrated impact and a track record of working closely with wet-lab or clinical teams.Skills: Strong Python, plus fluency with modern ML/CV libraries such as PyTorch, TensorFlow, scikit-learn and OpenCV. A solid grounding in statistics and experimental design. Proven ability to collaborate and communicate across matrixed, cross-functional teams. Preferred QualificationsDomain impact: Background in animal health, pharma or biotech R&D, with impactful ML/CV work such as chemoinformatics, bioinformatics or digital biomarkers, shown through projects, publications or patents.Technical depth: Hands-on experience with neural networks and generative models, and with operationalizing models at scale using Databricks and MLOps tooling.Leadership: A record of leading cross-functional teams, mentoring junior scientists and influencing scientific and technical direction in large, global organizations. DetailsTravel: Up to 10%Location: United States (details shared with shortlisted candidates)‍