Senior ML Engineer, Biologics Discovery – AI/ML Ops

6084-Janssen Research & Development, LLC Legal Entity; Spring House (PA); On-site; USD 109,000 - 175,000; Full time

Benefits offered by this job

Medical

Dental

Vision

Life insurance

Disability

401(k)

Job summary

Johnson & Johnson Innovative Medicine seeks a Senior ML Engineer for the Biologics Discovery Data Science team, based at Spring House, PA (preferred) or other US/EU locations. You will enable AI/ML workflows by deploying model-ready data and governance across discovery environments.

You will apply CI/CD, reproducibility, and observability practices to productionize AI capabilities, collaborating with scientists and partners to accelerate biologics discovery.

Qualifications

• Required degree in Computer Science, Engineering, Data Science, Machine Learning, or a related field.
• 4+ years of production AI/ML experience, including deployment and governance.
• Strong Python and modern AI/ML tooling experience.
• Experience with cloud platforms and data infrastructure for AI/ML workloads.

Responsibilities

• Build and operate scalable pipelines delivering model-ready data to ML/AI workflows.
• Establish governance, monitoring, and lifecycle management across development and production environments.
• Implement deployment automation, reproducibility, and traceability for AI solutions.
• Collaborate with data scientists and partner teams to productionize AI capabilities for discovery workflows.

Skills

Python

CI/CD

Cloud infra

ML lifecycle

Model registries

Automation

Education

Bachelor's degree in Computer Science/Engineering/Data Science/ML

Tools

MLflow

Weights & Biases

Model registries

CI/CD tools

Job description

Johnson & Johnson Innovative Medicine seeks a Senior ML Engineer for the Biologics Discovery Data Science team, based at Spring House, PA (preferred) or other US/EU locations. You will enable AI/ML workflows by deploying model-ready data and governance across discovery environments.

You will apply CI/CD, reproducibility, and observability practices to productionize AI capabilities, collaborating with scientists and partners to accelerate biologics discovery.