At a Glance
- Tasks: Design and optimise ML models for personalisation and recommendations.
- Company: Join a global media company at the forefront of technology.
- Benefits: Flexible hybrid or remote work, competitive salary, and growth opportunities.
- Other info: Dynamic role with opportunities to lead experiments and innovate.
- Why this job: Make a real impact on user experience with cutting-edge ML technologies.
- Qualifications: Experience in ML lifecycle, Python, TensorFlow or PyTorch required.
The predicted salary is between 70000 - 90000 £ per year.
We're working with a global media company looking for a Senior ML Engineer to own personalisation end to end. You'll be shipping models to production, building the pipelines that feed them, and running the experiments that improve them, all in service of recommendation engines and ranking algorithms that directly impact user experience.
- Design, train and optimise ML models for personalisation and recommendations
- Build and maintain scalable data pipelines for feature engineering and model training
- Deploy and monitor models in production — performance, availability, relevance
- Lead A/B testing and offline experiments to drive continuous improvement
- Evaluate emerging research in deep learning and GenAI for real-world integration
Requirements:
- Full ML lifecycle experience — from development through to monitoring in production
- Python + TensorFlow or PyTorch
- Kubeflow, TFX or similar training frameworks
- Model serving experience — Triton, TorchServe, TF Serving
- Real-time streaming and high-volume data processing
- Strong grasp of recommendation systems and personalisation algorithms
- Familiarity with Generative AI in production settings
If this sounds like your kind of challenge, drop me a message.
Machine Learning Engineer (hybrid or remote) in London employer: Arrows
Join a leading global media company that champions innovation and creativity, offering a dynamic work culture where your contributions directly enhance user experiences through cutting-edge machine learning solutions. With opportunities for professional growth and a commitment to employee well-being, this role allows you to thrive in a hybrid or remote setting while working on impactful projects that shape the future of personalisation and recommendation systems.
