AI Lead

About the Role :

You will serve as the technical backbone for AI innovation across molecular modeling, simulation automation, predictive ML, and generative design. This role blends the rigor of scientific computing with the architectural leadership required to scale enterprise-grade AI systems for global pharma customers.

You'll mentor teams, architect ML infrastructure, and bring research-grade models into production with the reliability and elegance expected from a world-class deep-tech organization.

Key Responsibilities :

1. Technical Leadership & Architecture :

• Architect end-to-end ML systems for molecular property prediction, protein-ligand scoring, ADMET forecasting, and generative molecular design.
• Lead design decisions for GNN-based pipelines, transformer architectures, diffusion models, and hybrid physics-ML models.
• Build scalable ML infrastructure that integrates computational chemistry engines, force-field computations, and cloud-based simulation workflows.
• Define technical standards for data pipelines, model deployment, distributed training, and high-performance inference.

2. Research Translation & Scientific Integration :

3. ML Engineering & Deployment Excellence :

4. Collaboration & Cross-Functional Enablement :

5. Innovation & Strategic Impact :

Required Qualifications :

Hands-on mastery of :

PyTorch / TensorFlow, CUDA

Python (scientific stack)

GNNs, transformers, multimodal architectures

MLFlow, Airflow, Docker, Kubernetes, AWS / GCP / Azure

Distributed training frameworks

Experience deploying ML solutions in production at scale-preferably in scientific SaaS or enterprise platforms.

Ability to dissect scientific problems and translate them into robust, elegant technical solutions.

Preferred Qualifications :

(ref : iimjobs.com)