Manager – AI/ML (Machine Learning, Deep Learning and Computational Chemistry)
Experience – 10+ Years
Position Overview
We are seeking a highly skilled and motivated Manager with expertise in AI/DL/ML, AI-driven drug discovery, deep learning, and computational chemistry to lead a cross-disciplinary research team. The successful candidate will guide the design, development, and application of advanced AI/ML models for accelerating drug discovery, molecular design, and therapeutic development. This role requires both technical leadership and strategic vision to drive innovation in pharmaceutical R&D.
Key Responsibilities
- Leadership & Strategy
- Lead, mentor, and grow a team of AI scientists, computational chemists, and data engineers.
- Define research strategy and align project milestones with organizational drug discovery goals.
- Collaborate with medicinal chemists, biologists, and clinicians to integrate AI solutions into discovery pipelines.
- Research & Development
- Develop and apply cutting-edge deep learning models (e.g., graph neural networks, generative models, foundation models) for molecular property prediction, de novo drug design, and protein–ligand interactions.
- Utilize computational chemistry techniques (docking, molecular dynamics, QSAR, free energy perturbation, ADME/Tox modeling) to validate AI predictions.
- Design workflows combining AI + physics-based methods to accelerate candidate selection.
- Stay current with advancements in AI for drug discovery, cheminformatics, and molecular simulations.
- Collaboration & Communication
- Act as a bridge between computational and experimental teams to ensure smooth translation of AI insights into laboratory validation.
- Collaborate with external partners, academic institutions, and consortia.
- Present findings and strategy updates to leadership, stakeholders, and scientific committees.
- Operational Excellence
- Oversee data management, curation, and integration from chemical, biological, and clinical sources.
- Ensure reproducibility, scalability, and regulatory compliance in AI-driven workflows.
- Drive publications, patents, and intellectual property creation in the AI drug discovery space.
Qualifications
- Education: PhD in Computer Science, Computational Chemistry, Cheminformatics, Bioinformatics, or related field.
- Experience:
- 10+ years of experience in AI/ML for drug discovery or computational chemistry, including at least 2–3 years in a leadership role.
- Strong track record of applying deep learning models (transformers, GNNs, generative models) to drug discovery problems.
- Experience with drug design platforms, cheminformatics toolkits (RDKit, OpenEye, Schrodinger, MOE), and molecular simulation software.
- Proven ability to manage multi-disciplinary teams and deliver on complex R&D projects.
- Technical Skills:
- Expertise in Python, PyTorch/TensorFlow, Scikit-learn, DeepChem.
- Strong background in computational chemistry methods and molecular modeling.
- Knowledge of cloud computing (AWS, GCP, Azure) and high-performance computing environments.
- Soft Skills:
- Strong leadership, project management, and mentoring abilities.
- Excellent communication and collaboration skills.
- Strategic mindset with a passion for innovation in healthcare.
Preferred Attributes
- Prior experience in pharma, biotech, or AI-driven drug discovery startups.
- Publications/patents in AI drug discovery, deep learning in chemistry/biology, or computational drug design.
- Understanding of regulatory and translational challenges in AI-enabled therapeutics.