The Francis Crick have an exciting opportunity available for a Machine Learning Engineer???? to join one of the world’s leading research Institutes at a crucial time in its evolution, and play a definitive role in shaping it for the future. You will join us on a full time, 3 year contract, and in return, you will receive a competitive salary...
Machine Learning EngineerLondonThe Data + Science TeamAt Deliveroo we have a world-class data & science organisation, with a mission to enable the highest quality human and machine decision-making. We have over 200 Machine Learning Engineers, Data Scientists, Data Analysts, and Analytics Engineers working throughout the company in product, business and platform teams.We have a strong, active data science community, with...
Machine Learning Engineering ManagerLondonAbout the RoleAt Deliveroo we have an outstanding data science organisation, with a mission to enable the highest quality human and machine decision-making. We work throughout the company - in product, business and platform teams - using analysis, experimentation, causal inference and machine learning techniques. We are uniquely placed to use data to help make better decisions...
Machine Learning Researcher - LLM/VLMAre you a PhD-educated Machine Learning Researcher looking for a new opportunity? If so, our client, a global consumer electronics company, is actively expanding their team. This role is based at one of their flagship AI centres in Cambridge, Cambridgeshire.Key Responsibilities:As a Machine Learning Researcher, you will:Work on on-device LLMs and VLMs, as well as adaptive...
Job Title: Machine Learning & Data ScientistLocation: Reading, UK (Hybrid)Salary: Up to £80,000 per annumAbout Us: We are dedicated to enhancing the global growth and resilience of renewable energy transmission by delivering intelligent, autonomous robotic monitoring solutions for high-voltage assets. Our mission focuses on supporting power transmission operators worldwide with advanced technologies.Role Overview: We are seeking a Machine Learning &...
Machine Learning Engineer | Cybersecurity Startup (Open Source, AI)We’re hiring aMachine Learning Engineerto join an early-stage cybersecurity startup that's building the next-gen security assistant - open-source at its core, focused on automating repetitive workflows and making life easier for security teams!You'll be part of a tight-knit, ambitious team with a strong engineering culture and a track record of building widely...
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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.
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.
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.
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