Senior ML Engineer: Production ML & Platform Lead

Senior ML Engineer: Production ML & Platform Lead

Full-Time 60000 - 80000 Β£ / year (est.) No working from home possible
The Sage Group plc

At a Glance

  • Tasks: Lead the transition of ML models to scalable production services and manage the full lifecycle.
  • Company: Join The Sage Group plc, a leader in innovative technology solutions.
  • Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
  • Other info: Be part of a forward-thinking team with excellent career advancement opportunities.
  • Why this job: Make a real impact by driving cutting-edge ML projects in a dynamic environment.
  • Qualifications: Experience in ML engineering and strong skills in software integration and cloud management.

The predicted salary is between 60000 - 80000 Β£ per year.

The Sage Group plc is seeking a Senior ML Engineer to take technical ownership of the production ML environment in a hybrid Newcastle-based role. You will drive transition of experimental models to scalable, observable production services, owning the full lifecycle from automated training pipelines to real-time inference clusters and production-grade software integration.

You will lead design of CT/deployment pipelines, implement robust telemetry, and manage cloud costs with modern deployment.

Senior ML Engineer: Production ML & Platform Lead employer: The Sage Group plc

The Sage Group plc is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of Newcastle. With a strong focus on employee growth, you will have access to cutting-edge technology and opportunities to lead impactful projects in machine learning, all while enjoying a supportive environment that values work-life balance and professional development.

The Sage Group plc

Contact Details:

The Sage Group plc Recruitment Team

We think you need these skills to ace Senior ML Engineer: Production ML & Platform Lead

Machine Learning
Production ML Environment Management
Automated Training Pipelines
Real-Time Inference Clusters
Software Integration
CT/Deployment Pipeline Design
Telemetry Implementation