Senior ML Engineer: Scale Production ML Platforms

Senior ML Engineer: Scale Production ML Platforms

Full-Time 70000 - 90000 Β£ / year (est.) No working from home possible
Relay Technologies

At a Glance

  • Tasks: Own productionising ML models from training to live integration in logistics.
  • Company: Relay Technologies, a leader in innovative logistics solutions.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Join a dynamic team focused on cutting-edge technology and career advancement.
  • Why this job: Make a real impact by deploying high-impact ML in a fast-paced environment.
  • Qualifications: Experience in machine learning and strong collaboration skills required.

The predicted salary is between 70000 - 90000 Β£ per year.

Relay Technologies seeks a Senior Machine Learning Engineer to own productionising ML models end-to-end, from training pipelines to live integration in a fast-paced logistics network.

You will help build and mature the ML Platform, evolve serving architecture, and ensure reliable model performance with drift monitoring.

The role emphasizes collaboration with data scientists and deploying high-impact ML in production.

#J-18808-Ljbffr

Senior ML Engineer: Scale Production ML Platforms employer: Relay Technologies

Relay is an exceptional employer, offering a vibrant and intellectually stimulating work culture that prioritises creativity and collaboration. As a Growth Marketing Manager, you'll have the unique opportunity to drive impactful marketing strategies in a fast-paced environment, backed by significant investment and a mission to revolutionise logistics. With a commitment to employee growth and a focus on diversity and inclusion, Relay empowers its team members to experiment, learn, and thrive while making a meaningful difference in the e-commerce landscape.

Relay Technologies

Contact Details:

Relay Technologies Recruitment Team

We think you need these skills to ace Senior ML Engineer: Scale Production ML Platforms

Machine Learning
Productionisation of ML Models
Training Pipelines
Live Integration
ML Platform Development
Serving Architecture
Model Performance Monitoring