Join datatonic as a Machine Learning Engineer and be part of a dynamic team dedicated to leveraging data to drive intelligent decision-making. You will design and implement machine learning models, optimize algorithms, and collaborate with cross-functional teams to deliver innovative solutions.

Join datatonic as a Senior Machine Learning Engineer and be a pivotal part of our innovative team focused on transforming data into actionable insights. In this role, you will leverage your expertise in machine learning to develop and enhance algorithms, contribute to data-driven solutions, and collaborate with cross-functional teams to push the boundaries of data analytics.

Join Trainline as the Head of Machine Learning Engineering, where you'll lead our innovative machine learning initiatives. In this pivotal role, you will spearhead the development and implementation of advanced ML solutions that enhance our customer experience and optimize our operations.

Join Our Team as a Staff Machine Learning EngineerBecome an integral part of Deliveroo’s mission to revolutionize the shopping and dining experience with a focus on impact, innovation, and growth. Our talented Engineering teams tackle intricate technical challenges within a global, three-sided marketplace, developing and scaling systems that cater to millions of customers, riders, and partners daily.From advanced real-time logistics to robust infrastructure and marketplace optimization, we create and manage the technology that fuels Deliveroo’s expansive growth.We are seeking a Staff Machine Learning Engineer to join our dynamic London team (working in a hybrid model, 3 days in the office). In this pivotal role, you will design and construct intelligent decision-making systems that operate at a large scale, directly influencing the experiences of consumers, riders, and merchants.Explore our Engineering team and discover our motivations, work culture, and what you can expect as part of our community.Your ResponsibilitiesJoin the Consumer Pricing team to tackle complex pricing challenges at Deliveroo. We are advancing towards dynamic, personalized pricing strategies that take into account consumer behavior, loyalty programs, and real-time market conditions.Your daily tasks will include:Designing and developing high-performance machine learning and optimization systems that guide Deliveroo’s core decisions at scale.Leading the technical advancement of our pricing infrastructure, resolving architectural bottlenecks and integrating enhanced model inputs and decision variables.Creating algorithms to enhance real-time marketplace efficiency, including personalized elasticity models and delivery time forecasts.Collaborating closely with Product Managers and Data Scientists to convert complex business challenges into effective algorithmic solutions.Providing technical leadership across various product domains, identifying and prioritizing high-impact algorithmic enhancements.Mentoring and guiding fellow engineers, elevating technical standards and advancing our machine learning and optimization practices across the company.Qualifications for SuccessThe ideal candidate will possess strong expertise in several of the following areas, along with a desire to grow in others:

Join Faculty as a Machine Learning Engineer and be at the forefront of innovation in artificial intelligence. In this role, you will leverage your expertise in machine learning to develop and implement cutting-edge algorithms and models that drive impactful solutions across various industries.As a part of our dynamic team, you will work collaboratively to transform complex data sets into actionable insights, optimizing our products and enhancing client offerings. If you are passionate about technology and eager to make a difference, we would love to hear from you!

About AnthropicAt Anthropic, we are dedicated to developing reliable, interpretable, and controllable AI systems. Our goal is to ensure that AI technology is safe and beneficial for both users and society. Our rapidly expanding team consists of passionate researchers, engineers, policy experts, and business leaders collaborating to create advantageous AI systems.About the TeamsThe Reinforcement Learning teams at Anthropic spearhead our research and development in reinforcement learning, playing an essential role in enhancing our AI systems. We have made significant contributions to all Claude models, particularly impacting the autonomy and coding capabilities of Claude Sonnet 4.5 and Opus 4.5. Our work encompasses several critical areas:Creating systems that empower models to utilize computers effectively.Enhancing code generation through reinforcement learning techniques.Conducting pioneering RL research for large language models.Establishing scalable RL infrastructure and training methodologies.Improving model reasoning capabilities.We work closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and secure. Additionally, we collaborate with the applied production training team to seamlessly integrate research advancements into deployed models, demonstrating our commitment to implementing research at scale. Our Reinforcement Learning teams operate at the intersection of cutting-edge research and engineering excellence, dedicated to building high-quality, scalable systems that expand the possibilities of AI.About the RoleAs a Research Engineer in the Reinforcement Learning domain, you will partner with a diverse group of researchers and engineers to enhance the capabilities and safety of large language models. This position merges research and engineering responsibilities, requiring you to implement innovative approaches while contributing to the research strategy. You will engage in fundamental research in reinforcement learning, developing 'agentic' models capable of tool use for open-ended tasks such as computer usage and autonomous software generation, improving reasoning skills in disciplines like mathematics, and creating prototypes for internal applications, productivity, and evaluation.Representative Projects:Design and optimize core reinforcement learning infrastructure, from clean training abstractions to distributed experiment management across GPU clusters, scaling our systems to manage increasingly complex research workflows.Invent, implement, and evaluate novel training environments, evaluations, and methodologies for reinforcement learning.

Join Almedia as a Machine Learning Engineer, where you'll be at the forefront of innovation in artificial intelligence and machine learning technologies. Your role will involve designing and implementing machine learning models to solve complex real-world problems. Collaborate with a talented team of engineers and data scientists to enhance our products and services through cutting-edge algorithms and data-driven solutions.

Role overview The Staff Machine Learning Engineer at AccuRx will work onsite in London (Shoreditch). The main focus is on creating and deploying machine learning models that help improve patient care and make healthcare workflows more efficient. This work aims to benefit both patients and healthcare professionals. What you will do Design, build, and deploy machine learning models for healthcare use cases Collaborate with engineering, product, and clinical teams to shape solutions Contribute to projects that influence patient outcomes and support healthcare providers

Why Join Faculty?Founded in 2014, Faculty believes that artificial intelligence is the defining technology of our era. Over the years, we have partnered with more than 350 global clients, transforming their operations using human-centric AI solutions. Discover our impactful projects here.We prioritize innovation over trends, developing responsible AI that genuinely drives results. Our team offers unmatched expertise in technical, product, and delivery aspects, serving clients across various sectors including government, finance, retail, energy, life sciences, and defense.As our business expands rapidly, we seek individuals who share our intellectual curiosity and aim to create a meaningful legacy through technology.Join us in harnessing AI's potential and making a significant difference in its applications.About Our TeamOur Defence team is dedicated to developing and implementing human-centered AI solutions that provide our nation with a strategic advantage in defense. We collaborate closely with clients to deliver ethical and cutting-edge AI for high-stakes scenarios, ensuring the balance of global power critical to our freedoms.Due to the sensitive nature of our work with Defence clients, you will need to be eligible for UK Security Clearance (SC) and should be prepared to work on-site with these clients 2 to 4 days a week, which may involve travel across the UK.When not on client sites, you will enjoy the flexibility of working from our London office or remotely from any location within the UK.Role OverviewAs a Senior Machine Learning Engineer, you will spearhead the development and deployment of innovative AI systems for a diverse client base. Your responsibilities will include designing, building, and deploying scalable, production-quality ML software and infrastructure that adheres to stringent operational and ethical standards.This position requires a proactive, cross-functional approach, blending technical skills, engineering leadership, and strong client-facing abilities.

Join our dynamic team at comind as a Senior Machine Learning Engineer. In this pivotal role, you will leverage your expertise in machine learning and data analysis to develop innovative solutions that drive our business forward. You will collaborate with cross-functional teams to design, implement, and optimize algorithms that enhance our products and services.

Our Mission Dex exists to help people find work that matches their strengths and interests. Too many talented individuals feel disconnected from their jobs, leaving potential untapped. Dex aims to close this gap by using technology to connect people with opportunities where they can thrive. By supporting more people in doing what they love, we hope to build a happier and more productive world. We are beginning this journey by connecting ambitious software engineers with companies that value their skills. About Dex Dex is backed by investors such as a16z Speedrun, Concept Ventures, and angels from OpenAI, Wise, ElevenLabs, and Meta's board. Our team of 12 works out of the Borough of London. We value ambition, directness, and kindness, and look for people who are authentic and proactive. While we support flexible schedules, we typically meet in person around three times each week. Role Overview: Founding Machine Learning Engineer This position centers on machine learning engineering, not research or prompt engineering. A solid grasp of how embeddings represent meaning and how attention affects retrieval is important. Large language models (LLMs) are part of the toolkit, but the focus is on understanding and solving problems at the model level, not just using APIs. The main goal: build a system that can quickly and accurately stack-rank candidates for new roles in seconds. Ownership of the representations and scoring models that power Dex’s ability to match engineers with companies. The matchmaking engine developed will underpin future features, including candidate-focused products, automated outreach, and improved sourcing tools. Strong engineering skills are as important as machine learning expertise. What You'll Do Lead machine learning projects, delivering efficient and reliable systems. Location This role is based in London, with in-person collaboration expected several times a week.

AccuRx seeks a Senior Machine Learning Engineer to join the team in London (Shoreditch). This position centers on creating machine learning tools that help improve patient care and streamline healthcare processes. What you will do Design and build machine learning solutions aimed at supporting healthcare professionals and patients. Work closely with a talented team to develop technology that makes a real difference in healthcare delivery. Collaboration Teamwork is a key part of this role. Regular collaboration with colleagues ensures that the solutions developed are practical and impactful for real-world healthcare settings. Location This position is based in Shoreditch, London.

Waymo is a pioneering company in the field of autonomous driving technology, dedicated to becoming the most trusted driver in the world. Originating from the Google Self-Driving Car Project in 2009, Waymo has concentrated on developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and save lives lost to traffic accidents. The Waymo Driver supports our fully autonomous ride-hailing service and is adaptable across various vehicle platforms and applications. With over ten million rider-only trips and more than 100 million miles driven autonomously on public roads, complemented by tens of billions of miles in simulation across 15+ U.S. states, our experience is unparalleled.The Simulator team is at the forefront of creating cutting-edge simulations of real-world environments for the training and assessment of the Waymo Driver. We leverage machine learning to accurately model the real world, incorporating realistic agents (vehicles, pedestrians, cyclists, motorcyclists, etc.), road systems, traffic controls, and weather conditions. To enhance the precision and flexibility of our simulations, we utilize large foundation models trained on extensive datasets, enabling rapid setup and deployment of multiple scenarios for our driver.Our London-based team collaborates closely with our colleagues in Mountain View and Oxford to develop and enhance these foundation models and integrate them into various evaluation and training products. We are seeking talented research engineers eager to tackle these innovative challenges.In this hybrid role, you will report directly to an Engineering Manager.

Waymo, a pioneer in autonomous driving technology, is dedicated to becoming the world’s most trusted driver. Since its inception as the Google Self-Driving Car Project in 2009, Waymo has been at the forefront of innovation, developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility while significantly reducing the number of lives lost in traffic accidents. The Waymo Driver powers our fully autonomous ride-hailing service and is adaptable to various vehicle platforms and applications. With over ten million rider-only trips completed, fueled by our experience of autonomously driving over 100 million miles on public roads and tens of billions of miles in simulation across more than 15 U.S. states, we are transforming transportation.The Driver Understanding and Evaluation (DUE) team at Waymo is focused on creating comprehensive metrics to evaluate the Waymo Driver’s behavior in real-world scenarios. We are developing advanced technologies such as context and scene analysis to enhance our driving understanding, as well as augmenting real-world driving data to generate rare driving events. This includes building large-scale data infrastructures and improving components like agents and realistic simulators, which are pivotal for our technical strategies and methodologies in assessing the Waymo Driver's performance.The DUE Machine Learning team will develop and maintain scalable machine learning systems and simulation workflows, enhancing evaluation processes and developer onboarding experiences. By merging expert human insights with cutting-edge machine learning models, we will provide training and evaluation data across hundreds of metrics and components that define the Waymo Driver. We are seeking passionate researchers and software engineers eager to harness machine learning techniques to elevate the evaluation systems within our autonomous vehicles, driven by a relentless pursuit of performance improvement.This position reports to the Engineering Manager.

Join our innovative startup, semaloop, as a Founding Machine Learning Engineer. In this pivotal role, you will design, develop, and deploy cutting-edge machine learning algorithms that will shape the future of our products. We are looking for a passionate engineer who thrives in a dynamic environment and is eager to make a substantial impact from the ground up.Your responsibilities will include collaborating with cross-functional teams, conducting data analysis, and implementing models that drive our technology forward. If you're excited about building scalable solutions and have a solid foundation in machine learning, we'd love to hear from you!

Role Overview Spotify is looking for a Machine Learning Engineer focused on Personalization to join the team in London. This role centers on using data insights to improve how users interact with the platform and increase engagement. What You Will Do Work with teams across disciplines to build and refine machine learning models for content and recommendation personalization. Develop solutions that tailor Spotify experiences for millions of listeners around the world. Apply data-driven methods to inform product decisions and feature development.

Role overview Utility Warehouse is hiring a Senior Machine Learning Engineer in London. This role focuses on building and deploying machine learning models that support business goals and improve customer interactions. The position involves close collaboration with colleagues from different teams to deliver practical solutions. What you will do Design, develop, and implement machine learning algorithms Analyze data to identify patterns and opportunities for automation Work with software engineers and other stakeholders to integrate models into production systems Support decision-making by delivering insights from data-driven models

Spotify is hiring a Director of Machine Learning Engineering to guide the Surfaces Foundation team in London. This leadership role centers on driving the development and improvement of machine learning models that shape user experiences throughout the Spotify platform. Role overview This position involves managing a skilled engineering group dedicated to building and refining machine learning solutions. The work directly supports Spotify’s goal of delivering a more personalized and efficient platform for listeners. Key responsibilities Set the strategic direction for machine learning projects within the Surfaces Foundation team Oversee the design and deployment of new ML models to enhance user experiences Ensure successful implementation of advanced machine learning technologies across the platform Location This role is based in London.

About AIONAION is pioneering an interoperable AI cloud platform that is set to revolutionize high-performance computing (HPC) through its innovative decentralized AI cloud. Designed specifically for bare-metal performance, AION democratizes access to computational resources and delivers managed services, positioning itself as a comprehensive AI lifecycle platform—facilitating organizations from raw data to deployed models through its forward-deployed engineering approach.The global business landscape is undergoing a seismic transformation due to AI, with a skyrocketing demand for computational power. AION aspires to be the gateway for dynamic compute workloads by forging integration bridges with various data centers globally and re-engineering the compute stack with its cutting-edge serverless technology. We recognize the challenges enterprises face in balancing AI adoption with security needs and are committed to ensuring robust enterprise security and compliance by redesigning every aspect of our infrastructure, from hardware and network packets to API interfaces.With a leadership team that boasts high-caliber founders and significant venture capital backing, AION is establishing its core team across India and the UK while being headquartered in the US.Who You AreYou are a proactive ML engineer with 4-6 years of experience in developing and fine-tuning large language models (LLMs) and transformer-based architectures. You possess a strong focus on execution and enjoy tackling complex challenges at the intersection of machine learning research and production systems.Your expertise spans the entire ML development lifecycle—from data preparation and model fine-tuning to rigorous evaluation and optimization. You have a deep understanding of what drives model performance and how to systematically enhance model quality through experimentation. Familiarity with LLM fine-tuning (LoRA, QLoRA), RLHF pipelines, and comprehensive model evaluation is highly desirable. You exhibit strong ownership and initiative, coupled with a passion for developing production-ready ML models that have a global impact on thousands of developers.