About Insilico

Insilico Medicine is an end-to-end, AI-driven pharma/biotechnology company with a mission to accelerate drug discovery and development by leveraging our rapidly evolving, proprietary platform and models across biology, chemistry, and clinical development.

For more info, visit our website https://insilico.com 

About Role

Insilico Medicine seeks a Machine Learning Engineer (LLM/RL) to build and scale GenAI models for molecular tasks.

Place of work

Office based - Abu Dhabi (Level 6, Unit 08, Block A, IRENA HQ Building Masdar City, Abu Dhabi, United Arab Emirates

Reports to

ML team leader

Responsibilities

• Design and scale reinforcement learning fine-tuning workflows for LLMs, including RLVR/RLHF approaches.
• Build and optimize high-throughput transformer training pipelines across multi-GPU and multi-node environments.
• Adapt models to domain-specific drug discovery and molecular design tasks, such as molecular generation and property prediction.
• Lead experimental design, monitor core metrics, and communicate insights and findings through presentations and/or publications.

Education

• M.S., Ph.D., or equivalent relevant experience in Computer Science, Machine Learning, Computational Chemistry, or a related quantitative discipline.

Required Skills & Experience

• ML Engineering: At least 5 years of experience in ML engineering
• Transformers: Expertise in training and deploying large transformer models using PyTorch.
• RL Algorithms: Hands-on experience with PPO/DPO/RLOO/GRPO and other related policy gradient and preference-based optimization methods.
• Scalable Training Pipelines: Proficiency in data, model, context, and pipeline parallelism.
• Reward Integration: Practical experience developing diverse reward functions and reward models.
• Tooling & Collaboration: Excellent Python skills are necessary, along with experience using Hugging Face Transformers, TRL/RLlib/verl, DeepSpeed, vLLM, Docker, Sagemaker, and CI/CD workflows.

Desirable Skills

• Senior Level: At least two years in a senior position.
• Drug Discovery & Molecular Design: Background in chemistry, cheminformatics, structural biology, or experience with molecular generative models.
• Generative Models: Knowledge of diffusion, flow-based, and other generative models.
• Research Leadership: Track record of machine learning publications.