Experteer Overview
In this Senior ML Engineer role, you will operationalize AI/ML capabilities for Biologics Discovery, bridging data science with discovery scientists. You’ll implement scalable data pipelines, governance, and lifecycle practices to move models from prototype to production. You’ll partner with researchers and engineers to enable reliable, production-grade AI workflows and accelerate scientific discovery. This position emphasizes reliability, reproducibility, and automation within a leading healthcare innovator.

Compensaciones / Ventajas
• Build and operate scalable pipelines delivering model-ready data to ML, generative AI, and agentic workflows
• Enable closed-loop scientific learning by capturing and provisioning new data for downstream modeling and evaluation
• Establish production-grade deployment, serving, monitoring, access control, and lifecycle management for ML/AI across environments
• Implement versioning and reproducible releases with traceability across the ML lifecycle
• Set up monitoring, observability, alerting, and performance management for ML workflows and AI services
• Develop automated workflows for testing, release management, and environment management across AI/ML solutions
• Scale AI capabilities to handle larger data volumes and more autonomous discovery workflows
• Monitor production model behavior, data quality, drift, latency, and resource utilization




• Partner with data scientists and domain experts to define reliable integration patterns between data products and AI/ML workflows
• Enable reproducible training, fine-tuning, evaluation, and deployment capabilities for ML scientists and AI agents
• Contribute to standardization and best practices to accelerate transition from experimentation to production
• Support security, access control, AI governance, documentation, and cost management across AI/ML solutions

Responsabilidades
• Degree in Computer Science, Engineering, Data Science, Machine Learning, or related computational field
• 4+ years of experience operationalizing and scaling AI/ML solutions in production
• Strong Python proficiency for AI/ML workflows across training, fine-tuning, deployment, and serving
• Experience with cloud infrastructure and modern data platforms for AI/ML workloads
• Experience with model registries, experiment tracking, and ML lifecycle tools (e.g., MLflow, Weights u0026 Biases)
• Experience implementing production AI/ML practices: versioning, deployment automation, CI/CD, automated testing, observability, containers, orchestration, scalable compute
• Strong software development and automation practices and ability to partner with data scientists and domain experts

Requisitos principales
• medical, dental, and vision insurance
• life and disability insurance
• retirement plan (pension) and 401(k)
• vacation and personal time off
• paid holidays and sick leave

📌 Senior Machine Learning Engineer, Biologics Discovery (Madrid)
🏢 Johnson u0026 Johnson
📍 Madrid