The Senior AI/ML Data Engineer owns the production pipelines that turn unstructured text and documents into reliable, model-ready data for our team's Generative AI and Natural Language Processing (NLP) applications and services. Key focus areas will include engineering data products built from licensed scientific literature, patents, clinical trials, and more. You'll build and maintain ingestion and parsing pipelines for unstructured or semi-structured text data with data-quality checks built in, govern data lineage and usage compliance for AI applications, and configure the search indices built on this data. You'll also build shared pipeline components and deployment patterns used across the team. These data products support critical use cases spanning early-stage scientific research to post-market surveillance, including systematic literature reviews, competitive intelligence, target identification, and safety monitoring.
You'll work directly alongside the data scientists and scientific subject matter experts who use your data. You will have the autonomy to propose better ways to build, see your work accelerate research, and ultimately help bring therapeutics to patients. As you grow, you'll have opportunities to expand into emerging areas, such as large language model (LLM)-powered document parsing and metadata enrichment. The position is embedded within a cross-disciplinary team of data scientists, bioinformaticians, and engineers dedicated to using cutting-edge AI/ML and data science techniques to drive drug discovery and development.
In addition to building and maintaining our suite of tools, our team consults on how software capabilities, data products, and AI/ML can support the projects of our 5,000+ stakeholders (scientists, engineers, regulatory liaisons, data scientists, etc.) across our multi-national organization. We strive to enhance data science, NLP, and AI literacy across these groups.
As part of our work, our team has opportunities to coauthor internal and external presentations, white papers, manuscripts, and/or open-source code releases. We invest in your professional growth by providing access to specialized learning platforms, opportunities to attend industry conferences, participation in internal communities of practice, and the chance to learn the science of drug discovery and development directly from domain experts.
Amazon Web Services (AWS), Anomaly Detection, Data Engineering, Data Storage, Design Applications, Drug Discovery Research, GitHub, GitHub Actions, Machine Learning Operations, Python (Programming Language), Software Development, System Designs, Testing
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Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.
Regular
Hybrid
11/24/2026
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At MSD, known as Merck & Co., Inc., Rahway, NJ, USA in the United States and Canada, we are unified around our purpose: We use the power of leading-edge science to save and improve lives around the world. For more than 130 years, we have brought hope to humanity through the development of important medicines and vaccines. We aspire to be the premier research-intensive biopharmaceutical company in the world – and today, we are at the forefront of research to deliver innovative health solutions that advance the prevention and treatment of diseases in people and animals. We foster a diverse and inclusive global workforce and operate responsibly every day to enable a safe, sustainable and healthy future for all people and communities. For more information, visit www.msd.com and connect with us on Facebook, Instagram, Twitter, and YouTube.