Senior Machine Learning Engineer, Biologics Discovery
Johnson & Johnson · Spring House, Pennsylvania, United States of America
📍 Spring House, Pennsylvania, United States of Americavia workdayFirst listed here 2026-09-28
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At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com .
As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.
Job Function:
R&D Product Development
Job Sub Function:
R&D Machine Learning
Job Category:
Scientific/Technology
All Job Posting Locations:
Beerse, Antwerp, Belgium, Madrid, Spain, Raritan, New Jersey, United States of America, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of America
Job Description:
Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.
Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.
Learn more at https://www.jnj.com/innovative-medicine
About the Opportunity
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
Why this role matters:
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.
Position Summary
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.
Why This Role Is Unique
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.
Key Responsibilities:
AI/ML Operations & Lifecycle Management
Build and operate scalable pipelines and interfaces that deliver model-ready data to ML, generative AI, and agentic workflows.
Enable closed-loop scientific learning by ensuring newly generated scientific data can be captured, governed, and made available to downstream modeling, evaluation, and agentic workflows.
Establish reliable operational capabilities for model deployment, serving, monitoring, access management, and lifecycle management across development and production environments.
Implement model, data, and workflow versioning, with reproducible releases, rollback capabilities, and traceability across the AI/ML lifecycle.
Reliability, Observability & Scale
Establish monitoring, observability, alerting, and performance management practices for ML workflows, deployed models, and AI services.
Develop and maintain automated workflows supporting testing, release management, environment management, and operational excellence across AI/ML solutions.
Enable AI capabilities to scale with growing scientific data volumes, computational demands, and increasingly autonomous discovery workflows.
Monitor model and system behavior in production, including data quality, model performance, drift, latency, reliability, and resource utilization.
Partnership & Standards
Partner with data scientists, technology teams, and domain experts to establish reliable integration pa
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