Machine Learning Engineer, Valuations (Basé à London)

Jobleads
London
4 weeks ago
Create job alert

About Motorway

Motorway is the UK's fastest-growing used car marketplace - our award winning, online-only platform connects private car sellers with over 7,500 verified dealers nationwide, who compete to offer the best price. Founded in 2017, our technology makes the process refreshingly easy, earning us an 'Excellent' Trustpilot rating with over 70,000 reviews. We're not just building a platform; we're changing how people sell cars.

Backed by leading investors like Index Ventures and ICONIQ Growth, and following a successful $190 million funding round, we're on a mission to transform the used car market.

About the team

We're redefining how cars are valued and sold online, and our mission is to make the process as simple and enjoyable as a Sunday drive. We're a tight-knit, data-driven bunch who love tackling complex challenges with innovative solutions. Our work directly impacts thousands of car sellers and dealers daily, ensuring they get the best possible deal. We're looking for a talented Machine Learning Engineer to join our journey and help us build the future of vehicle pricing.

About the role

  1. Develop and Deploy Machine Learning Models:You'll design, build, and deploy robust machine learning models that power our vehicle pricing service. Think XGBoost, GPs, and Bayesian models, all running smoothly on GCP and Vertex AI.
  2. Build and Maintain Production ML Systems:You'll ensure our backend systems and APIs deliver real-time pricing predictions across all platforms, 24/7. We're talking high-performance, scalability, and stability.
  3. Collaborate Effectively:You'll team up with data scientists, analysts, and engineers to solve challenging pricing problems. You'll also partner with our Infrastructure team to align with company-wide best practices.
  4. Drive Innovation:You'll be a key player in shaping the future of our pricing architecture. We encourage you to stay curious about emerging technologies (including generative AI) and bring your innovative ideas to the table.

About you

  1. ML Experience:You've deployed ML models at scale and have a good understanding of state-of-the-art regression and probabilistic models.
  2. Technical Skills:You're proficient in Python (pandas, scikit-learn, fastAPI/flask, pydantic, DVC) and SQL. You also have a strong knowledge of systems design, including serverless and event-driven microservice architecture.
  3. Engineering Excellence:You're passionate about writing clean, maintainable code and have strong practices within the context of ML, including OOP, abstraction, error handling, and logging.
  4. Cloud and Tools:You're familiar with ML lifecycle tools like Kubeflow and cloud platforms (GCP, Vertex AI, AWS). You also have experience with CI/CD pipelines (e.g., GitHub Actions), Docker, and IaC tools (e.g., Terraform).
  5. Testing and Evaluation:You have experience building ML evaluation frameworks and writing tests (unit, integration).
  6. Ownership and Collaboration:You have a strong sense of ownership, autonomy, and a highly organised nature. You're also a great team player and communicator.

You could be a great fit if

  1. You're proficient in Typescript/JavaScript and Node.js.
  2. You're passionate about building and deploying machine learning models that have a real-world impact.
  3. You're a creative problem-solver who loves tackling complex challenges.
  4. You're a team player who thrives in a collaborative environment.
  5. You're excited about the future of vehicle pricing and want to be part of a company that's redefining the used car marketplace.

Our interview process

  1. Qualifying Screen - 30 minutes
  2. Hiring Manager Interview - 60 minutes
  3. Technical Assessment - 60 minutes
  4. Final Interview (onsite depending on team) - 60 minutes

We'll get back to you within a week of each interview stage. You can chat with a talent partner throughout the process if you have any questions or need anything at all.

#J-18808-Ljbffr

Related Jobs

View all jobs

Machine Learning Engineer, Valuations

Principal Machine Learning Engineer (Basé à London)

Principal Machine Learning Engineer London, England (Basé à London)

Senior Software Dev Engineer, VariationsX (Twister) (Basé à London)

Senior Software Dev Engineer, VariationsX (Twister) (Basé à London)

Data Analytics Engineer

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.

Machine‑Learning Jobs for Non‑Technical Professionals: Where Do You Fit In?

The Model Needs More Than Math When ChatGPT went viral and London start‑ups raised seed rounds around “foundation models,” many professionals asked, “Do I need to learn PyTorch to work in machine learning?” The answer is no. According to the Turing Institute’s UK ML Industry Survey 2024, 39 % of advertised ML roles focus on strategy, compliance, product or operations rather than writing code. As models move from proof‑of‑concept to production, demand surges for specialists who translate algorithms into business value, manage risk and drive adoption. This guide reveals the fastest‑growing non‑coding ML roles, the transferable skills you may already have, real transition stories and a 90‑day action plan—no gradient descent necessary.

Quantexa Machine‑Learning Jobs in 2025: Your Complete UK Guide to Joining the Decision‑Intelligence Revolution

Money‑laundering rings, sanctioned entities, synthetic identities—complex risks hide in plain sight inside data. Quantexa, a London‑born scale‑up now valued at US $2.2 bn (Series F, August 2024), solves that problem with contextual decision‑intelligence (DI): graph analytics, entity resolution and machine learning stitched into a single platform. Banks, insurers, telecoms and governments from HSBC to HMRC use Quantexa to spot fraud, combat financial crime and optimise customer engagement. With the launch of Quantexa AI Studio in February 2025—bringing generative AI co‑pilots and large‑scale Graph Neural Networks (GNNs) to the platform—the company is hiring at record pace. The Quantexa careers portal lists 450+ open roles worldwide, over 220 in the UK across data science, software engineering, ML Ops and client delivery. Whether you are a graduate data scientist fluent in Python, a Scala veteran who loves Spark or a solutions architect who can turn messy data into knowledge graphs, this guide explains how to land a Quantexa machine‑learning job in 2025.