Senior ML Engineer (Biologics Discovery)

Location: Office-based in Spring House, Pennsylvania; Titusville or Raritan, New Jersey; Beerse, Belgium; or Madrid, Spain. No remote option.

Base pay: €55,400–€87,860 annually.

Company

Johnson & Johnson develops healthcare, pharmaceutical, and MedTech solutions, including innovative medicines and technologies for complex diseases.

What you will do

• Build and operate scalable pipelines and interfaces connecting model-ready scientific data with ML, generative AI, and agentic workflows.
• Enable deployment, serving, access management, monitoring, governance, and lifecycle management for AI/ML solutions.
• Implement model, data, and workflow versioning with reproducible releases, rollback capabilities, and end-to-end traceability.
• Establish observability, alerting, performance management, and automated testing and release workflows.
• Enable AI capabilities to scale across growing scientific data volumes, computational demands, and autonomous discovery workflows.
• Partner with data scientists, AI/ML practitioners, technology teams, and domain experts to establish reusable production patterns and standards.

Requirements

• Degree in Computer Science, Engineering, Data Science, Machine Learning, or a related computational field.
• At least 4 years of experience operationalizing and scaling AI/ML solutions in production.
• Strong Python skills and experience with model training, fine-tuning, evaluation, deployment, and serving workflows.
• Experience with cloud infrastructure, modern data platforms, model registries, experiment tracking, and ML lifecycle management tools such as MLflow or Weights & Biases.
• Experience with model versioning, deployment automation, CI/CD, automated testing, observability, monitoring, containers, orchestration, and scalable compute environments.
• Ability to work from one of the listed office locations; remote work is not available.

Nice to have

• Experience in pharmaceutical, biotechnology, or life sciences sectors.
• Exposure to real-time or near-real-time pipelines and instrument data integration.
• Experience with FAIR data principles, metadata management, data lineage, provenance, and AI-ready data practices.

Culture & Benefits

• Inclusive work environment centered on diversity, dignity, and individual contribution.
• Annual bonus or sales commission opportunities depending on pay grade and location.
• Vacation, parental, bereavement, caregiver, and volunteer leave.
• Well-being reimbursement and financial, physical, and mental health programs.
• Insurance plans, service anniversary awards, and recognition awards subject to applicable plans and location.