Hassan Sirelkhatim
Machine Learning Engineer- Genomics Drug Discovery at NVIDIA
London, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolHassan Sirelkhatim is a machine learning engineer and solutions architect with eight years of experience specializing in genomics and drug-discovery applications of large-scale AI. At NVIDIA he designs and optimizes training pipelines on supercomputers (e.g., Selene), accelerates transformer/GNN and LLM models for SMILES, DNA and proteins, and has delivered notable performance gains in deep learning basecalling (Bonito). He blends hands-on model optimization with customer-facing work, supporting sales and translating research prototypes into scalable deployments. His background spans industry and academia—from bioinformatics and insurance mathematics degrees to mentoring and reviewing deep RL and data science projects—giving him a rare mix of domain expertise and production ML engineering. An underappreciated strength is his experience tuning models across specialized sequence languages (molecules, genomes), enabling practical drug-discovery accelerations rather than just theoretical advances.
8 years of coding experience
5 years of employment as a software developer
Bachelor's degree, Insurance Mathematics, Bachelor's degree, Insurance Mathematics at University of Copenhagen
English, Arabic, Danish
Github Skills (10)
computational-biology8
docking8
binding8
transformation7
gpu5
machine-learning5
drug-discovery5
pytorch5
diffusion-models4
deep-learning3
Programming languages (3)
Github contributions (5)
MolecularAI/MolBART
Mar 2021 - Feb 2022
Pretrained SMILES transformation model for finetuning for diverse molecular tasks.
Contributions:1 review, 48 commits, 1 PR in 11 months
transformationdiversefinetuningsmilesmolecular
sirelkhatim/LSTM-Nasdaq-stock-prediction
Dec 2017 - Nov 2018
Contributions:10 pushes, 1 branch in 10 months
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