Machine Learning Engineer for Biomedical Text Analysis

Description du poste

We are seeking a highly motivated and experienced Machine Learning Engineer / AI Developer to join our team. This role focuses on developing and optimizing large language models (LLMs) for biomedical text analysis, knowledge extraction, and multi-modal data integration.

Responsabilités

• Design, train, and fine-tune LLMs for biomedical text analysis, knowledge extraction, and multi-modal data integration.
• Collaborate with domain experts to translate pharma R&D challenges into AI-driven solutions (e.g., literature mining, target validation, predictive modeling).
• Stay updated on SOTA LLM architectures (e.g., Transformer variants, retrieval-augmented models) and adapt them for biomedical use cases.

Key qualifications include:

• A PhD in Computer Science, Machine Learning, Bioinformatics, or related fields, or an exceptional Master's graduate with relevant experience.
• Strong understanding of LLM architectures (Transformer, BERT, GPT, etc.) and NLP techniques (tokenization, embeddings, attention mechanisms).
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow, JAX).

Additional preferred qualifications include:

• Prior exposure to biomedical / healthcare data (e.g., scientific literature, clinical trials, omics).
• Familiarity with B2B AI product development cycles (requirement gathering, prototyping, enterprise deployment).

This role offers the opportunity to work closely with cross-functional teams of AI researchers, scientists, and software engineers to deploy scalable, industry-leading AI tools. The ideal candidate will have a strong mindset for collaboration, adaptability to fast-paced R&D, and a curiosity about AI-driven drug discovery.