Job Title: Computer Vision & Machine Learning Engineer, Photon-Efficient Event-Driven Imaging Company: Snap Inc. Job Category: Machine Learning Roles & Responsibilities: Snap’s Spectacles unit is a world\-class Research \& Development team, working together to pave the way for the future of the camera and wearable computing. We’re working on cutting\-edge capture and AR solutions and are inventing new ways in which computing will be overlaid on the world around us. The Spectacles Computer Vision Team works to solve some of the most important challenges in Computer Vision, Machine Learning, and Augmented Reality. As a Computer Vision \& Machine Learning Engineer on this team, you’ll work on solving tough challenges in ultra\-low\-light and high\-temporal\-resolution imaging, developing novel algorithms for photon\-efficient, event\-driven imaging systems for the next generation of wearable devices. We work on wearables and look to push the boundaries of what is possible. Working from our London office, you will be collaborating closely with other Snap hardware and software teams around the world. * Design, train, and deploy machine learning models and computer vision algorithms tailored for photon\-efficient, event\-driven imaging systems * Contribute to state\-of\-the\-art tracking, depth estimation, and SLAM and ML systems leveraging high\-temporal\-resolution event\-driven data * Develop novel photon\-efficient imaging features and algorithms for the next generation of AR Glasses * Research new machine learning and probabilistic techniques to improve speed, noise robustness, and accuracy of computer vision algorithms in photon\-efficient, event\-driven imaging systems Work with our computer vision team to deliver next\-generation detection (such as face, hand, body etc.) technology for augmented reality systems * Work Location: London, ENG, UK Availability: Full time

Job Title: Machine Learning Engineer Company: Entopy Job Category: Machine Learning Roles & Responsibilities: We are seeking a dynamic and innovative Machine Learning Engineer to join our forward\-thinking team. In this role, you will drive the development, deployment, and optimization of machine learning models that power cutting\-edge solutions across diverse data\-driven applications. Your expertise will help transform complex data into actionable insights, enabling smarter decision\-making and delivering impactful results. This position offers an exciting opportunity to work with advanced technologies and collaborate with talented professionals dedicated to pushing the boundaries of artificial intelligence and big data analytics. Entopy is a fast\-growing, award\-winning AI company transforming how some of the world's most critical infrastructure is managed and operated. Recently named AI SME of the Year at the 2026 National AI Awards, we're at the forefront of applying advanced artificial intelligence to some of the most complex operational environments in the world. In this role, you will work on a variety of projects, including developing predictive ML solutions, exploring and analysing data, conducting domain research, and contributing to R\&D initiatives to enhance our models and ML pipelines. * Design and develop ML solutions: Build innovative machine learning, AI, and data science solutions to address complex real\-world challenges. * Explore and analyse data: Extract, clean, analyse, and interpret complex datasets to uncover patterns, generate insights, and identify opportunities. * Build and deploy predictive models: Develop, test, evaluate, and deploy predictive models and ML solutions that deliver practical value. * Develop custom algorithms: Design and implement tailored algorithms and analytical models to support operational and strategic decision\-making. * Work across the ML lifecycle: Contribute to all stages of ML development, from problem definition and feature engineering to deployment, monitoring, and optimisation. * Drive continuous improvement: Enhance existing ML models, pipelines, and processes to improve performance, efficiency, and reliability. * Research and innovate: Explore emerging AI/ML technologies, experiment with new techniques, and contribute fresh ideas through research and development. * Work on technology that matters. Help transform how critical infrastructure operates, improving efficiency, resilience and sustainability. * Work with global leaders. Collaborate with some of the world's largest organisations, solving real operational challenges. * Join at an exciting time. We're entering a period of significant growth, creating opportunities for those joining us now. * Make a real impact. Work closely with our leadership and technical teams, with a genuine voice in shaping the business. * Grow with us. Develop your skills, take on new responsibilities and build your career as Entopy scales. * Be part of a great team. Join an ambitious, collaborative and supportive team that values hard work, fresh ideas and having fun along the way. If you're ambitious, curious and excited by the opportunity to work with world\-leading organisations while helping scale an innovative AI company, we'd love to hear from you. Work Location: Hybrid remote in Newmarket CB8 8QE Work Location: Newmarket, ENG, UK Availability: Full time

Job Title: Applied AI ML Data Scientist, Vice President - Payments Company: JPMorganChase Job Category: Machine Learning Roles & Responsibilities: Job Description Payments sit at the center of the global economy, connecting businesses and consumers around the world. You will join a team driving innovation in this fast evolving space as new technologies reshape how money moves. In this role, you will work at the forefront of modern machine learning and generative AI to deliver meaningful, lasting impact on global finance. You will partner closely with product, operations, risk, and technology teams to turn ideas into measurable outcomes. You will also have opportunities to mentor others and help shape how we build and operate production AI. As a Vice President Machine Learning Data Scientist in Payments Machine Learning, you will lead the design, development, and production deployment of machine learning applications, including generative AI and agentic systems, on cloud infrastructure. You will own end\-to\-end delivery from problem framing and experimental design through scalable MLOps, evaluation, governance, and integration with strategic systems. You will help set technical direction, establish reusable patterns, and ensure solutions are reliable, secure, and observable in production. You will mentor engineers and data scientists and translate complex technical work into clear decisions and outcomes for stakeholders. Job Responsibilities * Lead end\-to\-end delivery of machine learning and AI solutions for complex payments and banking operations problems, from discovery and framing to production rollout and lifecycle management * Develop innovative machine learning solutions, including generative AI and multi\-agent approaches, and define evaluation, safety, and monitoring strategies for production use * Own production deployment patterns including containerization, continuous integration and delivery, automated testing, model and prompt registries, model and version governance, monitoring and alerting, and rollback strategies * Architect and deploy scalable, reliable, and secure machine learning and large language model services integrated with strategic platforms and downstream consumers across APIs, batch, streaming, and event\-driven patterns, meeting service level objectives * Partner with product, operations, risk and control, and technology teams to influence roadmaps, align on requirements, and deliver data\-led transformations * Establish reusable, modular data science and machine learning capabilities that scale across use cases, including feature engineering, evaluation harnesses, prompt tooling patterns, agent frameworks, orchestration, and context and memory management * Provide technical leadership and mentorship through code reviews, design reviews, best practices, and upskilling across data science and engineering partners * Communicate with technical and non\-technical stakeholders, translating model outputs into decisions, tradeoffs, and operational plans * Maintain strong documentation for approaches, model cards, runbooks, and operational procedures About Us J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first\-class business in a first\-class way approach to serving clients drives everything we do. We strive to build trusted, long\-term partnerships to help our clients achieve their business objectives. About The Team J.P. Morgan's Commercial \& Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial \& Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. Work Location: Greater London, England, UK Availability: Full time

Job Title: Senior Research Scientist Company: YOTI Job Category: Machine Learning Roles & Responsibilities: Purpose of the Role: To work on projects in the fields of Computer Vision, Machine Learning and Deep Learning Role Dimensions: Reports to Head of R\&D / CTO; within R\&D team. Working Arrangements: This will be a hybrid role and you will be expected to work from our Aldgate office atleast 1 day a week. Principal Responsibilities: * Maintain an expert level knowledge of the related academic literature on large scale classification with deep learning and being up\-to\-date with recent advances. * To implement academic papers into functional prototypes. * Mentoring of junior R\&D team members on technical aspects, reviewing merge requests and assisting in the debugging of issues that can occur during model development. * Presenting the evaluated performance of models to people outside the R\&D team, i.e. to people in other teams. * A solid working knowledge of the Linux command line * Working with Docker, and the ability to create new docker images for specific use cases * The ability to work independently on the technical aspects of a self\-contained project, e.g. being able to develop a model from the specification for that model through to doing a thorough analysis of the trained model Stage 2 : Call with the hiring manager (45 minutes) * Hybrid Working: Enjoy the best of both worlds with a blend of home working and time spent in our central London, dog\-friendly office. * Core Working Hours: We focus on outputs, not clock\-watching. Our core hours support the flexibility you need for a genuine work\-life balance. * Work from Anywhere: Want a change of scenery? Take advantage of our policy to work remotely from abroad for short periods. * Generous Annual Leave: 25 days holiday as standard, plus your Birthday Off to celebrate properly. * "Yotiversary" Days: Loyalty rewarded \- earn up to three additional paid days off based on your length of service. * Enhanced Parental Leave: We support growing families with up to six months’ fully paid maternity leave, 2 weeks of paid paternity leave plus a further four weeks of enhanced flexibility and time off, and enhanced parental provisions. Feel free to ask for more details! * Wellbeing Support: Access to trained, in\-house Mental Health First Aiders whenever you need a confidential chat, plus a fully comprehensive Employee Assistant Program. * Personal Development Budget: A dedicated, individual training budget to spend on your professional growth, plus quarterly YOTI Afternoons dedicated entirely to your professional development. * “Selfie Time": Paid time off every year to focus on volunteering, charity work, or personal passion projects. * Matched Fundraising: Double your impact \- we match charitable fundraising contributions made by our team. * Unpaid Sabbatical: Career breaks available for long\-term travel or personal resets after continuous service. This is a great opportunity to join a company that is leading the way for innovative and responsible identity verification. We’re looking for people who can adapt to a fast\-paced environment, as well as champion our brand and what we stand for. We value a positive attitude and people who have a collaborative, creative and transparent approach to solving problems. For more information about how we manage your data please read our Applicant Privacy Notice. Work Location: London, ENG, UK Availability: Full time

Job Title: Machine Learning Engineer Company: Optimove Job Category: Machine Learning Roles & Responsibilities: Recognized as a Visionary in Gartner's Magic Quadrant, we partner with leading brands like Sephora, Staples, and Entain. Today, more than 500 Optimovers across NYC, London, Tel Aviv, Scotland, Brazil, Estonia, and beyond are building the future of marketing together, in an environment that actively encourages ownership and growth, with two out of every three managers promoted from within. About the Role This is a role for an engineer who's ready to own meaningful, medium\-sized pieces of our personalisation roadmap end\-to\-end \- from problem framing through to deployment and monitoring \- and trusted to do so with minimal oversight. It's not solo delivery: you'll be working closely with a dynamic team spanning ML, MLOps and software engineering, and should be happy to contribute at every level, from early\-stage research through to production support. Role \& Core Responsibilities * Own the delivery of medium\-sized ML features end\-to\-end within Personalize \- problem framing, data preparation, model build/train, evaluation, deployment and monitoring \- to predictable timelines. * Develop predictive ML models for classification, ranking and personalisation, working with our text data. * Leverage LLMs and other state\-of\-the\-art techniques to enhance product capabilities. * Operationalise models as APIs across real\-time and batch environments. * Monitor production models in your own scope, treating data quality issues and model degradation as a priority. * Research new ML applications and improve pre\-existing models, sharing findings with the wider ML, MLOps and engineering team. * Collaborate closely with product, MLOps and engineering teams to define and prepare new ML applications, contributing meaningfully to planning and grooming. * Proactively surface and resolve technical and data challenges before they affect delivery, model quality or customers. * Exposure to a wide range of ML domains, including large\-scale search, ranking, Natural Language Processing, hybridisation, classification and text data processing. * Working with modern ML technologies, including LLMs, to enhance our products. * Fully real\-time architecture for data processing, model development and deployment. * Deploying and enhancing ML frameworks, optimising for inference and training/retraining cycles. * Online testing of models with live data, using our proprietary A/B/N testing technology to see quickly what performs well. * A supportive, collaborative team spanning ML, MLOps and software engineering, where rapid experimentation is the norm. * Dedicated time to research new methods, build proofs\-of\-concept, and ship to production quickly when they work. * Everyday use of modern AI coding assistants (e.g. Claude) to speed up experimentation and review. This role sits on the in\-role path towards Senior Machine Learning Engineer. As you grow, you'll deepen your expertise in our core ML stack, take on end\-to\-end ownership of larger features, represent the team in cross\-functional planning with MLOps and software engineering. Optimove offers a vibrant, people‑first culture where innovation, ownership, and continuous learning shape everything we do. Our UK team enjoys a modern office with a hybrid work model, daily lunch budget when onsite, and a fully stocked kitchen, along with a wide range of social events throughout the year. We're committed to helping our people grow in an inclusive, supportive workplace recognised as one of the UK's Best Workplaces in Tech and for Wellbeing. Work Location: Dundee, SCT, UK Availability: Full time

Job Title: Lead Data Scientist - Scams Prevention Company: Wise Australia Investments Job Category: Machine Learning Roles & Responsibilities: Wise is a global technology company, building the best way to move and manage the world’s money. Job Description We’re looking for a Lead Data Scientist to join our growing Scams Prevention team. This role is a unique opportunity to work behind the scenes of company transactions, understand how we mitigate risk and at the same time provide our customers with the seamless service they deserve. What you build will have a direct impact on Wise’s mission and millions of our customers. As a Lead Data Scientist in the Scam Prevention team, you will leverage your expertise in data science to innovate and deploy models that detect and prevent fraudulent activities. Your work will directly influence our ability to safeguard our platform against unauthorised access and enhance our overall security framework. You will collaborate closely with cross\-functional teams, including engineering, product, and security operations. Key Responsibilities: * Lead the development and deployment of advanced machine learning models to detect, predict, and mitigate account takeover attempts. * Analyse large volumes of data to identify trends, patterns, and anomalies associated with potential ATO and Send Scam threats. * Design and implement experiments to evaluate the effectiveness of fraud detection systems and continuously improve their performance. * Collaborate with security analysts and engineers to translate business and security requirements into actionable data insights and solutions. * Develop robust data pipelines, algorithms, and tools to support real\-time detection and response to ATO and Send Scam threats. * Stay informed about the latest advancements in data science, machine learning, and fraud prevention techniques to ensure state\-of\-the\-art capabilities in ATO and Send Scam. * Mentor and guide junior data scientists, fostering a culture of collaboration and continuous learning within the team. Find out more about our team, how we work and other open roles. Work Location: London, ENG, UK Availability: Full time

Job Title: Machine Learning Engineer - Python & LLM Systems Company: Permutable Job Category: Machine Learning Roles & Responsibilities: Our work connects developments across energy, commodities, economic policy and geopolitics to the assets and markets they influence. Behind it are demanding engineering problems: interpreting unstructured information, evaluating model behaviour and running reliable pipelines as new data arrives. * Build production LLM pipelines. Develop systems spanning data preparation, model training and fine\-tuning, evaluation, deployment and ongoing monitoring. * Improve model performance. Use Python and our in\-house GPU infrastructure to experiment with model architectures and fine\-tuning approaches, assessing quality alongside latency and compute requirements. * Make evaluation part of development. Build repeatable evaluations, investigate failure cases and use the results to guide model and pipeline improvements. * Orchestrate data and model workflows. Build and maintain Apache Airflow pipelines, with monitoring, retries and clear approaches to failure recovery. * Deploy and operate AI services. Work with AWS services including Lambda, ECS/EKS, S3 and Redshift, supported by Docker, GitHub Actions and Pulumi. * Take responsibility for what you build. Follow your work through deployment, monitor its behaviour in production and resolve problems with the team. * Contribute to engineering decisions. Bring ideas, test assumptions and help choose practical approaches to the next technical challenge. * Work on a substantial technical challenge. Help turn large volumes of changing, unstructured information into intelligence financial institutions can use. * Have a voice in what gets built. Work directly with our founder and engineers, contributing to model choices, evaluation methods and system design. * Develop across the full ML lifecycle. Build experience in experimentation, GPU\-based training, cloud deployment and production operations. * See the outcome of your work. Your models and pipelines will become part of a live product, with responsibility extending beyond the initial deployment. * At least two to three years of professional AI/ML engineering experience, or equivalent experience delivering substantial, relevant systems. * Strong Python skills and software engineering fundamentals, including maintainable code, testing, debugging and version control. * Hands\-on experience building, training or fine\-tuning machine learning models, with a clear understanding of how to evaluate their performance. * Experience taking models or AI pipelines into production and understanding what is needed to keep them working reliably. * Familiarity with MLOps practices, including CI/CD, containerisation, automated testing and monitoring. * A grounding in computer science, engineering, machine learning, mathematics or a related discipline, developed through study or practical experience. * Curiosity, initiative and the ability to work through unfamiliar problems. You’re comfortable discussing trade\-offs, asking questions and taking responsibility for delivery. * Work on a substantial technical challenge. Help turn large volumes of changing, unstructured information into intelligence financial institutions can use. * Have a voice in what gets built. Work directly with our founder and engineers, contributing to model choices, evaluation methods and system design. * Develop across the full ML lifecycle. Build experience in experimentation, GPU\-based training, cloud deployment and production operations. * See the outcome of your work. Your models and pipelines will become part of a live product, with responsibility extending beyond the initial deployment. * Join a close\-knit team with a strong startup culture. We share ideas, help each other solve problems and enjoy spending time together, with regular staff socials, offsites, sports events and office treats. * Share in what you help build. Equity options give you a stake in Permutable’s long\-term growth and success. Work Location: London, ENG, UK Availability: Full time

Job Title: Machine Learning Engineer Company: Hirivo Job Category: Machine Learning Roles & Responsibilities: You'll join a small applied\-AI team and own the ML behind Hirivo. That covers the job\-matching and ranking models, the LLM agents that read job adverts and fill application forms, and the systems that tell us whether they're working. You'll take features from prototype to production, then measure and monitor them. * Build and improve LLM\-powered agents that read job adverts and application forms and complete them accurately from a candidate's profile and CV (tool use, multi\-step workflows, handing questions to the candidate when needed). * Build job\-to\-candidate matching and ranking using embeddings, retrieval (RAG) and vector search, behind the campaign match score. * Create evaluation sets and automated evals for form\-fill accuracy, match quality and agent success rate, then iterate on prompts, models and fine\-tunes. * Train, fine\-tune and benchmark models (PyTorch), for example to parse CVs and job descriptions and to classify job fit. * Deploy models and agents as scalable APIs and services on the cloud (AWS/GCP) with Docker, Kubernetes and CI/CD, integrated with our Node backend. * Add observability: tracing of agent runs, latency/cost dashboards, failure and drift monitoring. * Build data pipelines that collect and clean job listings from many sources. * Work with product and with candidates to turn real job\-seeker problems into shipped features, and care about responsible AI: candidates' data, fairness and accuracy. * Building LLM evaluation frameworks (evals, benchmarks, LLM\-as\-judge). (40%)* * Monitoring and observability tooling (e.g. Datadog, OpenTelemetry, LangSmith). (55%)* * Open\-source contributions or a public portfolio of AI projects. (36%)* * A second language such as TypeScript, Go, C\+\+ or Rust. (TypeScript/JS 31%, Go 16%)* * GPU / CUDA / inference\-performance optimisation. (22%)* * Fine\-tuning (LoRA, RLHF/DPO). (18%)* * Familiarity with AI safety or responsible AI. (21%)* * Recommender/ranking systems, MLOps tooling (MLflow, model registry), web scraping/data pipelines. (13\-15% each)* Work Location: Hybrid remote in London Work Location: London, England, UK Availability: Full time

Job Title: AI Developer Company: CloudiQS Job Category: Machine Learning Roles & Responsibilities: Join our innovative team as an AI Developer and be at the forefront of transforming data into actionable insights through cutting\-edge artificial intelligence solutions. In this role, you will design, develop, and deploy advanced machine learning models and natural language processing systems that drive impactful business decisions. Your expertise will help shape the future of intelligent applications, leveraging a diverse set of technologies to solve complex problems with precision and creativity. This paid position offers an exciting opportunity to work on high\-impact projects in a dynamic environment committed to technological excellence and continuous learning. Duties * Develop and optimize machine learning algorithms using frameworks such as TensorFlow and PyTorch to enhance AI capabilities across various applications. * Design and implement scalable data pipelines utilizing big data tools like Hadoop, Spark, and SQL databases to manage large datasets efficiently. * Collaborate with cross\-functional teams to translate business needs into technical solutions, including natural language processing (NLP) models for language understanding tasks. * Conduct data mining and exploratory data analysis to uncover patterns, trends, and insights that inform model development. * Write clean, efficient code in programming languages such as Python, Java, C, and Bash (Unix shell) to support model deployment and integration. * Utilize cloud services like AWS for deploying scalable AI solutions while ensuring security and performance standards are met. * Maintain comprehensive documentation of algorithms, data schemas, and system architecture for ongoing development and troubleshooting. Work Location: Remote Work Location: Remote, UK Availability: Full time

Job Title: Machine Learning Engineer Internship Company: G-Research Job Category: Machine Learning Roles & Responsibilities: As part of our engineering team, you’ll shape the platforms and tools that drive high\-impact research \- designing systems that scale, accelerate discovery and support innovation across the firm. ### Role purpose ### Key Responsibilities of the role include * Implementing ideas from published research papers * Writing custom libraries to efficiently train models on petabytes of data * Reducing model training times by hand optimising machine learning operations * Profiling custom machine learning architectures to identify performance bottlenecks * Evaluating the latest hardware and software in the machine learning ecosystem Work Location: London, England, UK Availability: Full time