Bioinformatics - Manager with - AI/ML
About The Position
Soft Skills Deep curiosity and excitement about connecting AI architectures with biological meaning. Excellent cross-disciplinary communication — able to converse equally well with AI engineers and biologists. Self-directed, detail-oriented, and comfortable working in a fast-paced, dynamic startup environment. Passionate about improving patient outcomes through innovative science and technology. Technical Skills Programming: Expert in Python (pandas, PyTorch, TensorFlow, scikit-learn, Hugging Face, PyTorch Geometric). AI/ML Expertise: Proficiency in LLMs, GNNs, transformers, and model fine-tuning workflows. Bioinformatics Tools: Familiar with databases such as Ensembl, UniProt, ChEMBL, DrugBank, GEO, and OMIM. Data Integration: Experience with multi-omics data fusion and biomedical knowledge graphs. Visualization & Communication: Skilled in building interpretable visualizations and clearly communicating computational findings. Version Control: Proficient in Git and collaborative coding practices. Familiarity with molecular modeling, chemoinformatics, or AI for protein–ligand interaction prediction. Experience in biomedical NLP, scientific literature mining, or ontology construction. Understanding of preclinical pharmacology or toxicogenomics. Experience working in cloud environments (GCP, AWS). Regards, Mohammed ilyas, PH - 229-2644024 or Text - 229-469-1455 or you can share the updated resume at Mohammed@vtekis. com Additional Information All your information will be kept confidential according to EEO guidelines.
Requirements
- Expert in Python (pandas, PyTorch, TensorFlow, scikit-learn, Hugging Face, PyTorch Geometric).
- Proficiency in LLMs, GNNs, transformers, and model fine-tuning workflows.
- Familiar with databases such as Ensembl, UniProt, ChEMBL, DrugBank, GEO, and OMIM.
- Experience with multi-omics data fusion and biomedical knowledge graphs.
- Skilled in building interpretable visualizations and clearly communicating computational findings.
- Proficient in Git and collaborative coding practices.
- Familiarity with molecular modeling, chemoinformatics, or AI for protein–ligand interaction prediction.
- Experience in biomedical NLP, scientific literature mining, or ontology construction.
- Understanding of preclinical pharmacology or toxicogenomics.
- Experience working in cloud environments (GCP, AWS).
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What This Job Offers
Career Level
Manager
Education Level
No Education Listed
Number of Employees
5,001-10,000 employees
