Role Overview
We’re looking for a Senior AI Engineer who is passionate about transforming healthcare through cutting‑edge technology. In this role, you will make hands‑on contributions to the design, development, and deployment of advanced Machine Learning (ML) and Natural Language Processing (NLP) solutions powering Patient Finder. You’ll work on high‑impact initiatives including Generative AI, Named Entity Recognition and Linking (NER/NEL), multilingual NLP, and continuous learning on complex healthcare datasets. This is a unique opportunity to help define the future of AI in healthcare, with deep technical ownership and end‑to‑end responsibility for production‑grade ML solutions.
Key Responsibilities
- Design, build, and maintain robust, scalable ML and NLP solutions for production environments.
- Contribute hands‑on to the codebase, implementing high‑quality, production‑ready AI systems.
- Collaborate closely with cross‑functional engineering teams to ensure seamless integration of AI components with our search engine and data warehouse.
- Apply best practices in software engineering, including testing, observability, and CI/CD for ML systems.
- Support the internationalization and localization of NLP components across multiple languages.
- Work with the Product Owner and engineering stakeholders to translate business requirements into high‑quality ML deliverables.
- Research, evaluate, and apply state‑of‑the‑art NLP and ML methodologies.
- Share expertise with peers, contribute to knowledge‑sharing sessions, and informally mentor junior engineers.
IQVIA is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries. We create intelligent connections to accelerate the development and commercialization of innovative medical treatments to help improve patient outcomes and population health worldwide. Learn more at https://jobs.iqvia.com
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Requirements
- 6+ years of industry experience in AI/NLP, with a strong track record of delivering production‑grade solutions.
- Strong proficiency in Python for ML and NLP; experience with Go, Rust, or Java is a plus.
- Solid software engineering fundamentals and experience integrating ML systems into large‑scale production environments.
- Deep expertise in supervised and unsupervised learning, deep learning, and NLP.
- Experience deploying, monitoring, and maintaining production ML/NLP systems.
- Ability to clearly communicate complex technical concepts to cross‑functional teams.
- Strategic mindset for data science product planning under uncertainty.
- Holistic understanding of end‑to‑end ML pipelines within broader system architectures.
- Strong problem‑solving and critical thinking skills.
