Machine Learning Engineer Python AWS

Client Server
London
2 days ago
Create job alert

Machine Learning Engineer (Python AWS MLOps) Remote UK to £90k

Are you a tech savvy Machine Learning Engineer with experience of implementing ML algorithms into production?

You could be progressing your career in a senior, hands-on role as part of a friendly and supportive international team at a growing and hugely successful European car insurance tech company as they expand their UK presence; their platform enables an insurance quote to be made to the consumer within 60 seconds, using just 4 clicks.

As a Machine Learning Engineer you'll join a cross functional team, collaborating with Data Scientists and Software Engineers on complex insurance underwriting and pricing systems. They'll be a range of projects including data modelling and implementing Machine Learning algorithms, with Greenfield projects in the pipeline around forecasting and pricing.

There's a collaborative team Agile environment where you'll participate in technical discussions and have your voice heard, there's also opportunities to mentor other more junior team members if desired.

Location / WFH:

The company is a big advocate of flexible working and prides itself on DEI; you can go into the London office as often or as little as desired and can work fully remotely from anywhere in England; you can also work at times that suit you.

About you:

  • You are a data savvy Machine Learning Engineer with advanced Python coding skills and a strong knowledge of AWS
  • You have experience of across the full lifecycle of ML model development including into production
  • You're collaborative, enjoy problem solving and working with others to overcome technical challenges
  • You have a good knowledge of modern software engineering best practices, microservices, TDD / DDD, common Design Patterns
  • Experience with Databricks, PostgreSQL, Amazon RedShift or MLflow would be great but not essential

What's in it for you:

As a Machine Learning Engineer (Python AWS) you will earn a competitive package:

  • Up to £90k salary
  • Remote working including flexible working hours
  • Workplace nursery scheme
  • Enhanced maternity package
  • 25 days holiday plus ability to buy or sell 5 days p/year + extra "duvet day"
  • Pension, Private Medical and Dental Insurance, Life Assurance, Employee Assistance Programme
  • Weekly Yoga and monthly Acupuncture sessions, Headspace membership
  • Diverse, inclusive team environment with a range of support networks
  • A range of other perks including Perkbox, cycle to work, season ticket loan

Apply now to find out more about this Senior Machine Learning Engineer (Python AWS MLOps) opportunity.

At Client Server we believe in a diverse workplace that allows people to play to their strengths and continually learn. We're an equal opportunities employer whose people come from all walks of life and will never discriminate based on race, colour, religion, sex, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. The clients we work with share our values.

Q1NSLkRldkZFT1NKYXZhLjQ4NDM4LjEyMjcxQGNsaWVudHNlcnZlcm1lcmN1cnkuYXBsaXRyYWsuY29t.gif

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer (Manager)

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 AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

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

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.