Senior Machine Learning Engineer at Faculty | London

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

Longshot Systems builds advanced platforms for sports betting analytics and trading. The team blends software engineering, machine learning, and expertise in sports markets to develop trading strategies for clients. Role overview The Sports Betting Trading Analyst joins the modeling team as a subject matter expert in sports and betting markets. This role works closely with software engineers and machine learning specialists to refine and improve trading strategies. Key responsibilities include monitoring client trading activity, analyzing historical trade data, and applying deep knowledge of the sports betting landscape to spot improvements and value leaks in both current and new strategies. What you will do Work with engineers and machine learning specialists to enhance trading strategies Analyze historical trades and client activity to identify areas for improvement Apply expertise in sports and betting markets to find value opportunities and leaks Use data analysis tools, especially Python and Jupyter notebooks, to extract insights Engage with a wide range of sports from a betting perspective Requirements Strong passion for sports and sports betting, ideally with experience as a professional bettor Deep understanding of betting exchanges, prediction markets, and sharp bookmakers, including US and Asian markets Proficiency with Jupyter notebooks and data analysis in Python Strong numerical skills and a solid background in statistics Interest in following a broad range of sports, especially through the lens of betting Working arrangements This position follows a hybrid working model. Thursdays require in-person attendance at the London (Farringdon) office, while the rest of the week offers flexibility. Core hours are 10 am to 6 pm UK time, Monday through Friday, with support for flexible working to help the team meet goals. The role often benefits from engagement during sporting events, and tools are available to review games outside regular hours. Interview process Introductory call (30 minutes) to discuss background and interests First technical interview (90 minutes) for an in-depth discussion of experience Comprehensive assessment day (10:00 am - 6:00 pm) on-site, focused on data analysis using Python to generate insights

Join Longshot Systems, where we are at the forefront of developing sophisticated platforms for sports betting analytics and trading.We are in search of talented Machine Learning Researchers to join our quantitative modeling team. This team’s primary objective is to enhance the predictive capabilities of our models using historical event and market data. The quality of our models is paramount, as improvements directly influence our company’s success.In this role, you will design, test, and implement innovative machine learning models using Python, continuously enhancing our existing state-of-the-art solutions. As a small, focused company, we offer you the chance to be involved in every aspect of the R&D process, from high-level design to production implementation.The ideal candidate will possess high creativity and enjoy developing new, innovative approaches to problem-solving, and will have the autonomy to explore the most suitable methods for the challenges at hand. A strong mathematical foundation in machine learning and core statistics is essential. While knowledge of sports betting is not required, experience with modeling sports — particularly in-play football, basketball, or tennis — is advantageous.We embrace a hybrid working model, requiring in-office presence on Thursdays at our London (Farringdon) office, while allowing flexibility for the remainder of the week. Our standard working hours are from 10 am to 6 pm UK time, Monday to Friday, with support for flexible schedules to help our team achieve their goals.Our interview process includes:Introductory call (30 mins) - discussing your background and interestsTechnical interview (60 mins) - focusing on modeling questions and a coding exerciseFull assessment day (10:30 am – 5 pm) - encompassing a comprehensive modeling exercise and team interactions

Join Longshot Systems, where we are pioneering cutting-edge platforms for sports betting analytics and trading.We are looking for enthusiastic Graduate Machine Learning Researchers to become integral members of our quantitative modeling team. This team is dedicated to enhancing the predictive capabilities of our models using historical event data, as the excellence of our models is crucial to our company’s success.In this role, you will be responsible for designing, testing, and implementing innovative machine learning models in Python while continuously refining our existing top-tier solutions. As a small, focused company, Longshot offers you the opportunity to engage deeply in all facets of the R&D process, from high-level design to production implementation, while also learning from experienced industry professionals.The ideal candidate will possess a creative mindset and thrive in generating novel approaches to problem-solving. You will have the autonomy to explore and research the most suitable methods for the challenges presented. A solid mathematical foundation in Machine Learning principles and core statistics is essential, though prior knowledge of sports betting is not a requirement.We embrace a hybrid working model, with in-office work on Thursdays at our London (Farringdon) location and remote work for the remainder of the week. Our regular working hours are from 10 AM to 6 PM UK time, Monday to Friday, with a strong emphasis on flexible working to empower our team to achieve their objectives.Our interview process consists of the following steps:Introductory call (30 mins) - Discuss your background and interestsTechnical interview (60 mins) - Engage in modeling discussions and scenario-based questionsFull assessment day (9:30 AM–5 PM) - Tackle a real modeling challenge utilizing near-production dataQualifications A PhD or research Master’s degree in a quantitative, technical discipline (e.g., Mathematics, Physics, Machine Learning) from a reputable university Proficiency in modeling tabular data using Python Benefits Participation in an uncapped company bonus scheme, typically ranging from 10-20% of salary based on experience 10% matched pension contributions Private healthcare coverage Long-term illness insurance Gym membership Choice of hardware and setup for your development environment

Join Longshot Systems Ltd, where we create cutting-edge platforms for sports betting, analytics, and trading. We are seeking a Senior DevOps Engineer to enhance our platform team.You will manage a medium-sized deployment that connects with global sports betting platforms and supports multiple internal teams with diverse infrastructure needs. Your role will involve overseeing critical systems from backtesting to real-time trading and long-running backend services.Our infrastructure is hosted on AWS, and we are undergoing an evolution focused on automation and repeatability to drive our growth. Our core systems process thousands of trading signals per second, requiring minimal latency, presenting similar challenges to high-frequency trading environments but in the sports betting sector.As a Senior DevOps Engineer, you will collaborate closely with the CTO and development team to maintain our production and development trading infrastructure. You will take the lead on developing new infrastructure and troubleshooting performance and stability issues across applications, networks, and operating systems. You should be adept at analyzing metrics, packet dumps, and logs to identify and resolve issues, followed by implementing automation to prevent future occurrences.The ideal candidate is autonomous and innovative, thriving on generating new solutions and suggesting improvements to current methodologies. We offer you flexibility and the freedom to explore effective solutions.We embrace a hybrid work model, requiring in-office attendance on Thursdays at our London (Farringdon) office, with flexible arrangements for the remainder of the week. Our standard working hours are 10 AM to 6 PM UK time, Monday to Friday, with support for flexible schedules to achieve your goals.Regarding on-call responsibilities, while we do not maintain a 24/7 rota, we have a compensated on-call system based on best efforts, which will involve sharing responsibilities within the platform team.Interview Process:Introductory call (30 mins) – discuss your background and interests.First technical interview (30 mins) – live systems management and code review.Second technical interview (60 mins) – in-depth technical questions.Full assessment day (10:30 AM – 5 PM) – a practical systems engineering exercise reflecting actual team work. Meet the team, tour the office, and enjoy a complimentary lunch.

Join Longshot Systems, a pioneering company dedicated to developing cutting-edge platforms for sports betting analytics and trading.We are in search of a Senior Software Engineer to become a vital member of our trading platform team. As a small but highly focused organization, we seek an individual who can effectively architect and implement solutions to achieve our upcoming product, performance, and stability objectives. This role involves ownership of our technical standards, coding guidelines, CI/CD processes, observability, and security measures. If you are passionate about delivering features and enhancing the overall technical excellence of our team and platform, we want to hear from you.Our trading platform is responsible for integrating with numerous bookmakers and exchanges globally, normalizing and consolidating global odds data across various sports for internal trading strategies. We manage thousands of odds updates and trades per second, maintaining stringent standards for latency, correctness, and feed quality. You will be at the forefront, integrating additional trading venues, optimizing key platform components, and enhancing the safety and speed of trading. Our team also oversees a large historical data repository, supporting the company's broader trading and research initiatives.Our key platform systems are primarily built using Golang, featuring message buses and databases at the core of our architecture. While fluency in Golang is advantageous, it's not a prerequisite, as we have a team full of experts ready to assist you in learning.We embrace a hybrid work model, with Thursdays in our London office (Farringdon) and flexible arrangements for the rest of the week. Our standard working hours are 10 AM to 6 PM UK time, Monday through Friday, with support for flexible schedules to help our team achieve their objectives.

Why Join Faculty?Founded in 2014, Faculty believes that artificial intelligence is the defining technology of our era. With over 350 global customers, we have consistently demonstrated how human-centric AI can transform organizational performance. Discover our real-world impact here.We steer clear of fleeting trends and instead focus on innovating, constructing, and deploying responsible AI that delivers tangible results. Our extensive expertise spans technical, product, and delivery aspects, serving clients across diverse sectors including government, finance, retail, energy, life sciences, and defense.As our company and reputation continue to expand rapidly, we are eager to find individuals who share our intellectual curiosity and ambition to create a meaningful legacy through technology.Join us in harnessing AI's potential to craft powerful applications that can change the world.About Our TeamAt Faculty, our Life Sciences team focuses on developing AI solutions that streamline the research and commercialization processes for groundbreaking therapies. We collaborate with leading pharmaceutical companies, academic institutions, and MedTech startups to create solutions that address pressing healthcare challenges and promote equitable health access.Your Role:As a Senior Machine Learning Engineer, you will spearhead the development and deployment of advanced AI systems for our varied clientele. Your responsibilities will include designing, building, and implementing scalable, production-ready ML software and infrastructure that adheres to stringent operational and ethical standards.This dynamic, cross-functional role requires a unique combination of technical skills, engineering leadership, and client engagement capabilities.Key Responsibilities:Lead the technical scoping and architectural decisions for impactful ML systems.Design and construct production-grade ML software, tools, and scalable infrastructure.Establish and apply best practices and standards for deploying machine learning effectively.

Why Join Faculty?Founded in 2014, Faculty believes that artificial intelligence is the defining technology of our era. Since our inception, we have partnered with over 350 clients worldwide, helping them enhance their performance through human-centric AI solutions. Discover our impact here.We are not swayed by fleeting trends; we focus on developing and implementing responsible AI that truly makes a difference. Our expertise spans technical, product, and delivery domains, servicing clients across various sectors including government, finance, retail, energy, life sciences, and defense.As our business continues to grow rapidly, we seek intellectually curious individuals who are passionate about making a positive impact through technology.Join us in harnessing the power of AI and envisioning its most transformative applications.About Our TeamIn our Professional and Financial Services Business unit, we leverage over a decade of Applied AI experience to assist our clients in navigating an ever-evolving landscape. We create and integrate AI solutions that enhance operational efficiency, improve customer experiences, and unlock commercial opportunities in uncertain markets. Within the boundaries of highly regulated industries, we see vast potential for significant innovation and are proud to set the benchmark for combining technical excellence with secure deployment.Role OverviewAs a Senior Machine Learning Engineer, you will spearhead the development and deployment of advanced AI systems for our diverse clientele. Your responsibilities will include designing, building, and implementing scalable, production-ready ML software and infrastructure that adheres to stringent operational and ethical standards.This is a dynamic, cross-functional role that demands a mix of technical prowess, engineering leadership, and strong client engagement skills.Key Responsibilities:Overseeing technical scoping and architectural decisions for impactful ML systems.Crafting and developing production-ready ML software and infrastructure.

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:

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.

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.

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.

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.

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.

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

At G MASS Consulting, we proudly support a prestigious Audit and Advisory firm in their quest for innovation and excellence. We are seeking a Senior Machine Learning Engineer who will play a pivotal role in refining and expanding their pricing technology. In this influential role, you will be responsible for designing and managing machine learning platforms that enhance pricing workflows, facilitate quick model deployment, and ensure dependable model performance at scale. You will collaborate closely with our Data Science, Actuarial, and Product teams to drive impactful results.

Join Deliveroo as a Senior Machine Learning Platform Engineer, where you'll play a pivotal role in shaping the future of our machine learning capabilities. You will work alongside talented engineers and data scientists to build robust and scalable machine learning platforms that drive our business forward. Your expertise will help us leverage data to enhance our services, improve customer experiences, and optimize performance.

About UsAt Trainline, we are committed to revolutionizing travel by fostering a sustainable future. Our platform empowers millions of travelers to discover and book the most cost-effective tickets across various carriers and fares, utilizing our highly-rated mobile app, website, and B2B partner channels.Join Us on Our Journey As Europe’s leading downloaded rail app, we experience over 125 million monthly visits and facilitate £5.9 billion in annual ticket sales. Collaborating with over 270 rail and coach companies across more than 40 countries, we strive to make travel simple, seamless, eco-friendly, and affordable.As a FTSE 250 company, our diverse team of over 1,000 Trainliners hails from more than 50 nationalities and operates from key cities including London, Paris, Barcelona, Milan, Edinburgh, and Madrid. With a focus on growth across the UK and Europe, now is the ideal time to join us on this exhilarating journey.Elevating Machine Learning & AI at Trainline Machine learning is pivotal to our mission of enabling millions to make sustainable travel choices daily. Within our AI & ML community, we develop and maintain production-grade systems that enhance search, pricing, personalization, and marketing optimization while increasingly deploying intelligent AI agents to transform customer support and journey discovery.You will collaborate with a dynamic team of Machine Learning Engineers and Data Engineers on innovative GenAI initiatives, including our Travel Assistant—an AI-driven tool that assists customers with refunds, journey updates, and ticket conditions, alongside developing Voice AI agents for effective customer query handling.Our team merges robust ML principles with the latest LLM frameworks (LangGraph, LangChain), RAG architectures, MCP integrations, and production monitoring tools such as Braintrust, all deployed on AWS. We foster an environment that values ownership, curiosity, and thoughtful experimentation.Role OverviewIn this role, you will focus on the design, development, and operation of LLM-powered and predictive ML systems in production. You will work on AI systems like our Travel Assistant and Voice AI initiatives while contributing to traditional ML services owned by the team.

asos seeks a Machine Learning Engineer in London to advance technology solutions in online fashion retail. This role centers on building algorithms that enhance both product features and the customer experience. Key responsibilities Design and develop machine learning models for practical use in the retail sector Use data science methods to strengthen asos’s product offerings Collaborate with various teams to boost the efficiency and performance of core systems Role impact Your technical work will directly influence asos’s customers and day-to-day business. The solutions developed in this position help asos maintain a competitive edge as online fashion evolves.