Lead Machine Learning Engineer - Recommendation Systems

About SwapSwap serves as the backbone of contemporary agentic commerce, being the only AI-native platform that seamlessly integrates backend operations with an innovative storefront experience.Designed for brands looking to sell anything, anywhere, Swap centralizes global operations, enhances intelligent workflows, and empowers margin-protecting decisions through real-time data and capabilities. Our expansive product range covers cross-border transactions, tax solutions, returns, demand planning, and our state-of-the-art agentic storefront, providing merchants with complete transparency to act confidently.At Swap, we cultivate a culture that prioritizes clarity, creativity, and shared ownership as we transform the landscape of global commerce.About the RoleAs the Lead Machine Learning Engineer focusing on Recommendations, you will be responsible for shaping the intelligence behind the AI Storefront at Swap, determining what products are displayed to each shopper. This position is highly technical and hands-on, merging expertise in recommendation systems, large language models (LLMs), and fashion understanding. You will develop the models and pipelines that drive style-aware product recommendations, outfit generation, and personalized discovery, managing the entire process from research and prototyping to production systems that serve actual customers. Collaboration with our conversational AI layer will be essential, as you will extract insightful preference signals through dialogue and integrate these with traditional e-commerce behavioral data and LLM-based world knowledge to enhance recommendations, particularly addressing cold-start challenges in innovative ways.You will establish high technical standards for ML engineering in the recommendations domain at Swap, playing a pivotal role in the evolution of this team area as we scale.

ASOS seeks a Machine Learning Engineer in London to focus on recommendation systems. The main responsibility involves developing and refining models that deliver personalized product suggestions to customers. Key responsibilities Design and implement machine learning models that improve the relevance of product recommendations. Translate data insights into practical updates for recommendation algorithms, working alongside team members. Contribute to projects aimed at enhancing the user experience through smarter, more tailored suggestions. Collaboration This role involves partnering with colleagues in data science and engineering to share expertise and strengthen the performance of ASOS’s recommendation systems.

Role overview ASOS seeks a Senior Machine Learning Engineer to advance its recommendation systems. This team develops and enhances algorithms that deliver personalized product suggestions to a large customer base. What you will do Design, implement, and improve machine learning models focused on recommendations Collaborate with data scientists, software engineers, and product managers to create solutions that boost user engagement Work on algorithms that make shopping experiences more relevant and rewarding for ASOS customers Location This role is based in London.

Join our dynamic team at Faculty as a Lead Machine Learning Engineer. In this pivotal role, you will spearhead innovative machine learning projects while mentoring a talented team of engineers. You will be responsible for designing cutting-edge algorithms and developing scalable models to solve complex business challenges.The ideal candidate will possess a deep understanding of machine learning frameworks, proficiency in programming languages such as Python or R, and a passion for pushing the boundaries of technology. You will collaborate closely with cross-functional teams to ensure the successful implementation of machine learning solutions.

Wise seeks a Lead Machine Learning Engineer / Scientist based in London. This role centers on developing and refining machine learning models and algorithms that help drive data-informed decisions throughout the company. What you will do Build and enhance machine learning models to support Wise’s products and services. Collaborate with teams from various disciplines to deliver scalable, effective solutions. Apply advanced algorithms to improve decision-making and strengthen product offerings. Collaboration This position involves working closely with colleagues across the business, bringing together expertise from different areas to solve complex challenges and deliver impactful results.

At Longshot Systems, we develop cutting-edge platforms for sports betting analytics and trading.We are currently seeking experienced Machine Learning Engineers to join our modeling engineering team. In this role, you will collaborate closely with our quantitative research teams to transform prototype trading models into robust, production-ready systems. You will be responsible for designing and building the tooling, frameworks, and data engineering necessary to support strategy research and development, while also architecting high-level designs of the strategy software to minimize trading latency and ensure scalability. Our ML stack is primarily Python-based, incorporating modern ML libraries and tools such as Polars, Ray, and Plotly.The ideal candidate will possess a solid software engineering background, with extensive experience in high-performance computing topics such as multi-threading, networking, profiling, and optimization. Proficiency with the NumPy/SciPy stack is essential, along with experience in performance optimization tools like C++ and Numba. Familiarity with common ML algorithms and techniques is advantageous but not mandatory.As a hybrid working company, we require team members to work in our London (Farringdon) office on Thursdays, while offering flexibility for remote work on other days. Our standard working hours are from 10 am to 6 pm UK time, Monday to Friday, but we encourage flexible schedules to help our team meet their objectives.Interview Process:Introductory Call (30 mins) - Discuss your background and interestsFirst Technical Interview (30 mins) - Live code review and pair programmingSecond Technical Interview (60 mins) - In-depth technical questionsFull Assessment Day (10:30 am to 5 pm) - A programming exercise reflective of actual team tasks

Why Join Faculty?Founded in 2014, Faculty was established with the belief that artificial intelligence (AI) would be the defining technology of our era. Since then, we have partnered with over 350 global clients to enhance their operations through human-centric AI solutions. Discover our real-world impact here.We focus on genuine innovation rather than fleeting trends. Our team excels in creating and implementing responsible AI that delivers substantial results. We offer unmatched expertise in technical, product, and delivery aspects to a diverse clientele, including sectors such as government, finance, retail, energy, life sciences, and defense.As our business and reputation continue to expand rapidly, we seek individuals who share our passion for intellectual exploration and our commitment to creating a lasting positive legacy through technology.Join us at the forefront of AI technology, where you will have the autonomy to conceptualize its most impactful applications and bring them to life.About Our TeamOur Retail and Consumer team is committed to assisting clients in an industry that is being revolutionized by new technologies and shifting consumer expectations. With over a decade of experience in Applied AI, we blend exceptional technical and delivery skills to enable businesses to adapt and flourish.The RoleAs a Lead Machine Learning Engineer, you will take charge of the technical direction and execution of intricate, cutting-edge AI projects. You will serve as a technical authority, applying your expertise across diverse projects from AI strategy formulation to client-side implementations, while ensuring robust architectural decisions.This role requires a mix of advanced technical skills and leadership capabilities, emphasizing innovation, team development, and the creation of reusable solutions throughout the organization. If you are prepared to manage high-stakes projects and deliver practical, innovative results, this is your opportunity to influence our future.Your ResponsibilitiesEstablishing the technical trajectory for complex ML projects, managing trade-offs, and directing team priorities.Designing, implementing, and sustaining reliable, scalable ML/software systems while justifying crucial architectural choices.

Faculty, founded in 2014, focuses on using artificial intelligence to bring about meaningful change for clients worldwide. The company’s mission centers on developing responsible, human-centric AI solutions that have a real impact across sectors such as government, finance, retail, energy, life sciences, and defense. Faculty’s team brings strong technical, product, and delivery skills, working with over 350 global clients. More about their impact can be found here. Faculty values innovation that lasts, aiming to deliver AI that makes a genuine difference rather than following short-lived trends. The organization looks for people who share a curiosity for technology and a desire to leave a positive legacy. Division focus The Energy, Transition, and Environment team leads Faculty’s work in the clean energy sector. This division partners with major energy providers, GreenTech startups, and national infrastructure bodies to accelerate the move toward net-zero emissions and improve efficiency for utility companies. The team’s projects aim to deliver measurable, sustainable results through responsible AI use. Role overview The Lead Machine Learning Engineer will set technical direction and ensure the successful delivery of complex AI projects. This role involves shaping AI strategies, overseeing client implementations, and making key architectural decisions. The position combines deep technical expertise with leadership, fostering team growth and building reusable solutions across the company. What you will do Guide technical strategy for AI initiatives within the Energy, Transition, and Environment division Oversee project execution from initial strategy through client delivery Make architectural decisions to ensure reliability and scalability Mentor team members and support their development Contribute to reusable solutions that benefit the wider organization

Join our dynamic team as a Lead Machine Learning Engineer at Faculty, where you will spearhead innovative machine learning projects that drive impactful solutions. You will collaborate closely with cross-functional teams to design, develop, and deploy cutting-edge machine learning models that enhance decision-making processes. Your expertise will guide our data-driven initiatives, ensuring we remain at the forefront of technological advancement.

Why Join Faculty?Founded in 2014, Faculty is at the forefront of AI innovation, believing it to be the pivotal technology of our era. With a diverse portfolio of over 350 global clients, we are committed to enhancing performance through human-centric AI solutions. To learn more about our impactful work, click here.We prioritize innovation over fleeting trends, focusing on the development and deployment of responsible AI that drives tangible results. Our expertise in technical, product, and delivery aspects empowers clients across various sectors including government, finance, retail, energy, life sciences, and defense.As our business and reputation expand rapidly, we actively seek individuals who share our intellectual curiosity and ambition to leave a positive technological legacy.AI is a transformative force; join us to explore its most powerful applications and make them a reality.About Our TeamOur Energy, Transition, and Environment unit is leading the way in advancing the clean energy revolution. We aim to expedite the shift toward net-zero emissions and enhance efficiencies for the next generation of utility companies.We believe that the responsible and intelligent utilization of AI is essential for achieving our mission. Collaborating with a variety of clients—from major energy operators to GreenTech startups and national infrastructure providers—we create solutions that yield measurable impact, steering us toward a smarter, cleaner, and more sustainable future.Role OverviewAs a Lead Software Engineer focused on Machine Learning, you will guide the technical direction and execution of sophisticated AI projects. Your role will encompass serving as a technical authority, applying your expertise across numerous projects, from client-side deployments to strategic AI advisory, ensuring that architectural choices are robust and dependable.This position requires a blend of advanced technical skills and effective leadership, emphasizing innovation, nurturing team development, and crafting reusable solutions throughout the organization. If you are prepared to manage complex projects and deliver practical, innovative results, this is your opportunity to influence our future.Key Responsibilities:Establishing the technical direction and overseeing the development of AI projects.Leading a team of engineers, providing mentorship and fostering a collaborative work environment.Ensuring best practices in software development and design principles are adhered to.Engaging with clients to understand their needs and translating them into technical solutions.

About UsFounded in the United States in 2022 and now headquartered in London, UK, Recraft is revolutionizing the creative landscape with its cutting-edge AI tool designed specifically for professional designers, illustrators, and marketers. Our platform sets a new benchmark in image generation excellence.Our innovative tool empowers creators to swiftly generate and refine original images, vector art, illustrations, icons, and 3D graphics using AI technology. With over 3 million users across 200 countries, who have collectively produced hundreds of millions of images, Recraft is just at the beginning of its journey.Join us and explore a universe of professional opportunities! Contribute to large-scale projects and help shape the future of creativity. We are dedicated to making Recraft an indispensable daily tool for every designer, setting the industry standard. Our mission is to enable creators to fully control their creative process with AI, equipping them with innovative tools to turn their ideas into reality.If you are enthusiastic about pushing the boundaries of AI, we welcome you to join our team!

At Orbital Materials, we harness the power of AI to revolutionize data center hardware, ensuring our products consistently outperform the competition. Our advanced AI simulates materials at the atomic level, allowing us to evaluate millions of hardware configurations in the time it would typically take to assess just hundreds. This innovative approach enables us to discover optimal designs that surpass traditional benchmarks, resulting in hardware specifications that competitors cannot match: 1 MW/rack, PUE As each deployment generates valuable field data, our AI models become increasingly sophisticated. This creates a virtuous cycle where improved models lead to better hardware, which in turn enhances our AI capabilities. We are not merely benefitting from AI advancements; we are actively driving its pace.Our focus on data centers is driven by an urgent market need and demanding specifications. However, the AI-accelerated development processes we've established—spanning materials discovery, hardware design, and manufacturing optimization—are applicable to any complex physical system. Data centers serve as our initial proof point, not the limit of our ambitions.With operations in London, Canada, and the USA, we are assembling teams across various domains including ML research, product development, mechanical engineering, and chemical engineering. If you're eager to work at the intersection of AI and physical sciences, we'd love to hear from you.As a Staff Machine Learning Engineer at Orbital, you will be instrumental in architecting sophisticated AI systems for the multi-scale design of physical technologies. By multi-scale, we mean that we create world-class foundational models capable of simulating everything from the microscopic motion of atoms to the macroscopic flow of liquids in 1GW data centers. You will collaborate across these diverse scales, leveraging the creativity of our scientists and engineers, augmented by premier domain agents.In this pivotal role, you will establish exceptionally high technical standards and lead projects from initial prototypes to full-scale production deployment. We seek individuals who possess a passion for craftsmanship, a commitment to continual learning, and a drive to build scalable systems. Additionally, we value a low-ego mindset and a genuine enthusiasm for leveraging AI to tackle significant global industrial technology challenges.

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 the Future of AI at GraphcoreAt Graphcore, we're at the forefront of AI computing innovation. Our team, comprised of semiconductor, software, and AI specialists, is dedicated to building a comprehensive AI compute stack—from cutting-edge silicon to high-performance software and robust data center infrastructure. Backed by the SoftBank Group's substantial long-term investment, we are pioneering essential technologies within the burgeoning SoftBank AI ecosystem. As we expand globally, we invite you to collaborate with some of the brightest minds in the industry to tackle complex challenges and shape the future of artificial intelligence.Position OverviewAs a Senior Machine Learning Engineer on our Applied AI team, you will play a pivotal role in enhancing AI technologies by developing and optimizing machine learning models specifically designed for our advanced hardware. Your work will focus on large-scale systems where performance is paramount. Collaborating closely with our Software Development and Research teams, you will help identify innovative opportunities that set Graphcore's technology apart in the competitive landscape. We are looking for engineers with robust technical skills and a keen understanding of implementing AI models at scale, who are eager to make a significant impact in this rapidly evolving sector.About the TeamThe Applied AI team acts as advocates for our customers, ensuring that we stay abreast of the latest AI models, applications, and software to guarantee that Graphcore's technology integrates seamlessly into the AI ecosystem at scale. We develop reference applications, enhance essential software libraries—such as optimizing kernels for our hardware efficiency—and collaborate with our Research team to explore and publish groundbreaking ideas in areas like efficient computation, model scaling, and the distributed training and inference of AI models across various modalities and applications. If you are passionate about advancing the next generation of AI models on state-of-the-art hardware, we would love to connect with you!

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.