Senior ML Engineer – Life Sciences AI Solutions

Roche Holding AG; Welwyn; Híbrido; GBP 90.000 - 130.000; Jornada completa

Descripción de la vacante

Roche operates in Welwyn, UK, seeking a Senior Machine Learning Engineer to design, build, and scale AI/ML systems for drug discovery. The role collaborates with scientists, product managers, and DevOps to deliver data-driven solutions on a Kubernetes-based stack.

You'll apply ML theory, optimize performance, and contribute to data infrastructure, data pipelines, and governance, shaping architectures and ensuring robust backend services. Onsite three days per week.

Formación

• Master's or PhD in Computer Science or related field, or equivalent experience.
• Extensive experience in machine learning engineering and ML theory.
• Strong proficiency with AI/ML frameworks, libraries, and tools.
• Experience with Kubernetes, databases or data lakes, and cloud-native architectures (AWS).
• Excellent communication and collaboration with scientists and engineers.

Responsabilidades

• Design, develop, and test robust AI/ML-facing applications and backend systems.
• Build tools to evaluate AI/ML model performance and quality.
• Partner with product managers and scientists to translate needs into architectures.
• Develop and maintain data systems powering analytics and ML.
• Implement and evaluate new AI/ML algorithms and techniques.
• Contribute to architectural decisions and code reviews.
• Span the stack, building and improving systems beyond core area.

Conocimientos

ML engineering

Statistics

GPU optimization

Communication skills

Cloud architectures (AWS)

Educación

Master's or PhD in Computer Science or related field

Herramientas

Kubernetes

Relational Databases

NoSQL Databases / Data Lakes

Cloud platforms (AWS)

Python

Descripción del empleo

Roche operates in Welwyn, UK, seeking a Senior Machine Learning Engineer to design, build, and scale AI/ML systems for drug discovery. The role collaborates with scientists, product managers, and DevOps to deliver data-driven solutions on a Kubernetes-based stack.

You'll apply ML theory, optimize performance, and contribute to data infrastructure, data pipelines, and governance, shaping architectures and ensuring robust backend services. Onsite three days per week.