Senior Machine Learning Engineer

On
London
3 weeks ago
Create job alert
Overview

In short As a Senior Machine Learning Engineer, you\'ll build and automate production-level machine learning pipelines to drive our marketing programs at On. You\'ll partner with business, marketing, and data science teams to design, test, and deploy robust and scalable solutions. You will ensure our models are reliable and effectively integrated into our marketing technology stack. In the dynamic landscape of On Data, Machine Learning and AI play a crucial role in accelerating our business growth and operations.

We are enhancing our technology landscape to fuel the growth of On, helping to ignite the human spirit through movement.


Responsibilities

  • Drive impact through AI: Collaborate with data scientists to translate models into production-grade machine learning services that drive strong business impact through our marketing technology stack (e.g., email service providers, ad platforms, app platforms).
  • Platform excellence: Design, build, and maintain scalable and reliable data and model pipelines. Build an ML Ops infrastructure that monitors model performance and implement alerting to ensure high availability and accuracy.
  • Data culture: Work with cross-functional teams to understand business requirements and needs, and translate these into technical plans. AI/ML Best Practices: Contribute to the development of our MLOps best practices and infrastructure.

Your story

  • Technical Acumen: 6+ years of experience in implementing complex machine learning initiatives and independently designing production grade end to end ML/AI pipelines (e.g. Kubeflow, MLflow, Airflow). You have strong programming skills in Python.
  • Deep Machine Learning Expertise: Strong theoretical foundation and practical expertise in deep learning, embeddings, clustering models, and prediction.
  • AI platform Experience: Familiar with core components of AI platforms and have experience with production grade AI platforms and components (e.g. Vertex AI, Docker, Kubernetes).
  • Cloud and Platform Expertise: Experience with cloud-based machine learning platforms (e.g. GCP, AWS).
  • Team player: Ability to partner with data science and engineering team members; strong communication and interpersonal skills to convey complex technical information to diverse audiences.
  • Gen AI: Experience deploying Generative AI is a plus.

What We Offer

On is a place that is centered around growth and progress. We offer an environment designed to give people the tools to develop holistically – to stay active, to learn, explore and innovate. Our distinctive approach combines a supportive, team-oriented atmosphere, with access to personal self-care for both physical and mental well-being, so each person is led by purpose.


On is an Equal Opportunity Employer. We are committed to creating a work environment that is fair and inclusive, where all decisions related to recruitment, advancement, and retention are free of discrimination.


More

  • Seniority level: Mid-Senior level
  • Employment type: Full-time
  • Job function: Engineering and Information Technology
  • Industry: Retail


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.