Manager – AI/ML (Machine Learning, Deep Learning and Computational Chemistry)

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.

Work arrangement
No