Manager AI ML

Position Overview

Manager

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 proteinligand 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.