Senior Machine Learning Engineer

Haggerston
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer - Research

Senior Machine Learning Engineer

Senior Machine Learning Scientist

Senior Machine Learning Scientist

Senior Data Engineer - (Python & SQL)

Lead Data Engineer

Senior Machine Learning Engineer - London - Up to £120,000

With a focus on hands-on model building and implementation, the candidate will work closely with a Data Scientist and be part of an R&D team of seven, including the Head of Engineering, Product, and five engineers. This is a standalone role, and the engineer will be expected to be largely self-sufficient.

Responsibilities and Key Deliverables

  • Develop and maintain a ranking recommendation model that suggests recipes to users based on prior preferences, effectively serving as a product’s main feature.
  • Greenfield, meaning the engineer will build the machine learning models from scratch.
  • Full responsibility for ML model development, deployment, maintenance, and product integration.
  • The candidate must advise on frameworks, architect solutions, and ensure models are product-oriented and sustainable for the long term.

    Desired Candidate Profile
  • Minimum 4-5 years of hands-on experience with machine learning in a commercial environment, with strong decision-making capabilities regarding model architecture and deployment.
  • Preference for candidates with experience in B2C, subscription-based, or content-heavy start-ups, though experience with similar consumer products will also be considered.
  • Highly autonomous, with the ability to manage both product scoping and technical execution. The candidate should understand the demands of an early-stage product and be comfortable with an evolving role in a lean, start-up-style environment.

    Qualifications
  • The focus is on hands-on experience over academic background candidates should be skilled in implementing practical ML solutions.
  • A strong preference for candidates who are product-driven, with the ability to make decisions that align with long-term product goals.

    Interview Process
  1. Screening Call (30 mins) - Focus on culture fit and general understanding.
  2. Data Engineering Interview (45-60 mins) - Includes a take-home data task that candidates will analyse and present to the hiring manager and Data Scientist.
  3. Architecture Interview (45-60 mins) - Candidates will outline their approach to model architecture and decision-making.
  4. Offer Stage

    The salary on offer is between £90,000 to £120,000.

    If you are interested in the above, please apply or submit your CV to (url removed)

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.

Careers

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.

Jobs

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.

Careers Jobs

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.