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Johnson & Johnson Innovative Medicine is seeking a Senior ML Engineer for our Biologics Discovery Data Science team. This role builds and operates the integration, deployment, lifecycle management, and governance capabilities that enable machine learning (ML) models and AI solutions developed by partner organizations to run reliably in Biologics Discovery environments. You are the senior team member who closes the gap between model-ready data in our data warehouse and models that serve discovery scientists.
This position will be based at one of our office locations in either Spring House, PA (strongly preferred), Titusville, NJ, or Raritan, NJ, USA; Beers, Belgium, or Madrid, Spain. (No remote option.)
Please note that this role is available across multiple countries and may be posted under different requisition numbers to comply with local requirements. While you are welcome to apply to any or all of the postings, we recommend focusing on the specific country(s) that align with your preferred location(s):
USA - Requisition Number: R-099962
Spain - Requisition Number: R-100646
Belgium - Requisition Number: R-100647
The future of AI-native discovery depends on high-quality AI and data solutions that connect scientific data, machine learning models, and agentic workflows. This role will shape how enterprise AI and MLOps capabilities are adapted, integrated, and operationalized for Biologics Discovery, enabling AI solutions to scale from prototypes into trusted capabilities that accelerate scientific learning and therapeutic discovery.
In this role, you will enable AI/ML solutions to move reliably from development into production within Biologics Discovery. Working closely with data scientists, AI/ML scientists, discovery scientists, and partner organizations at J&J, you will own the deployment, lifecycle management, access, monitoring, and governance of ML, generative AI, and agentic solutions for discovery workflows. The role does not own core model development or the underlying enterprise platforms. Instead, it ensures that models and AI capabilities developed by partner teams are operationalized reliably for scientific use.
You will bring expertise in modern AI/ML operational practices, including reproducibility, CI/CD, observability, governance, automation, and scalable compute, helping adapt enterprise capabilities for discovery-specific use cases. Your work will enable reliable, production-grade AI workflows and accelerate the adoption of ML and agentic systems in biologics discovery.
This is a rare opportunity to play a key role in enabling AI-native Biologics Discovery. You will help operationalize and scale AI/ML capabilities that transform model-ready data and promising models into reliable, production-grade solutions that accelerate scientific discovery.