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Agentic AI Engineer Life Sciences - Healx
AI Engineer
Design and implement agentic AI workflows that accelerate rare‑disease drug discovery, leveraging Python, machine learning, cloud platforms, and bioinformatics to turn complex data into actionable therapeutic insights.
About the role
Key Responsibilities
- Develop and deploy autonomous AI pipelines that integrate heterogeneous biomedical data to identify novel therapeutic candidates for rare diseases.
- Design, train, and fine‑tune machine‑learning models (e.g., graph neural networks, language models) for target validation, compound prioritization, and predictive safety profiling.
- Build scalable, cloud‑native infrastructure (AWS/GCP) to support high‑throughput data processing, model serving, and continuous integration/continuous deployment (CI/CD) of AI workflows.
- Collaborate with pharmacologists, data scientists, and software engineers to translate deep pharmacology expertise into reproducible, production‑grade code.
- Implement monitoring, logging, and automated evaluation frameworks to ensure model reliability, interpretability, and regulatory compliance.
Requirements
- 5+ years of software engineering experience with strong Python proficiency and production‑grade ML libraries (TensorFlow, PyTorch, scikit‑learn).
- Demonstrated expertise in building end‑to‑end AI/ML pipelines for biomedical or life‑science applications.
- Hands‑on experience with cloud platforms (AWS, GCP, or Azure) and container orchestration (Docker, Kubernetes).
- Solid understanding of bioinformatics data types (genomics, proteomics, clinical data) and drug‑discovery processes.
- Track record of publishing or delivering AI solutions that improve decision‑making in a research or pharmaceutical setting.
Skills
pythonmachine learning