Machine Learning Engineer at Waymo | London, England

Waymo is at the forefront of autonomous driving technology, striving to become the world's most reliable driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has dedicated itself to developing the Waymo Driver—The World’s Most Experienced Driver™. Our goal is to enhance mobility access while preventing the tragic loss of life caused by traffic accidents. The Waymo Driver powers our fully autonomous ride-hailing service and is adaptable across various vehicle platforms and applications. To date, we've completed over ten million rider-only trips, with extensive experience driving autonomously over 100 million miles on public roads and conducting tens of billions of miles in simulation across more than 15 U.S. states.The Simulator team is responsible for creating cutting-edge simulations that mimic realistic environments to train and test the Waymo driver. Through advanced machine learning techniques, we model real-world scenarios, including realistic agents such as vehicles, pedestrians, cyclists, motorcyclists, and more, alongside roads, traffic systems, and weather conditions. By leveraging large foundation models, trained on our vast datasets, we can rapidly set up and deploy diverse scenarios to challenge our driver.We are excited to establish a team in London, UK, to collaborate with our colleagues in Mountain View and Oxford on enhancing these foundational models and integrating them into various training and evaluation tools. We seek enthusiastic research engineers eager to tackle these groundbreaking challenges.In this hybrid role, you will report directly to an Engineering Director.

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.

Waymo is an innovative leader in autonomous driving technology, striving to be the most trusted driver globally. Originating from the Google Self-Driving Car Project in 2009, our focus has been on developing the Waymo Driver—The World's Most Experienced Driver™—to enhance mobility access while significantly reducing traffic-related fatalities. The Waymo Driver underpins our fully autonomous ride-hail service and is versatile enough to integrate with various vehicle platforms and applications. With over ten million rider-only trips facilitated and a flawless record of driving over 100 million miles on public roads and tens of billions in simulation across more than 15 U.S. states, our mission is clear.The DUE ML Core London team is responsible for designing and maintaining robust machine learning systems, simulation workflows, and analytics tools aimed at enhancing evaluation processes and developer onboarding experiences. By merging expert human judgment with state-of-the-art machine learning models, we provide training and evaluation data for a multitude of metrics and components integral to the Waymo Driver.We are seeking passionate researchers and software engineers who are enthusiastic about advancing machine learning techniques for evaluation systems and driving performance enhancements throughout our technology stack.

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 is at the forefront of autonomous driving technology, dedicated to becoming the world's most trusted driver. Originally initiated as the Google Self-Driving Car Project in 2009, our team has been relentlessly working to enhance mobility access and save lives by developing the Waymo Driver—The World’s Most Experienced Driver™. With over ten million successful rider-only trips facilitated by our technology, which has driven over 100 million miles on public roads and tens of billions of miles in simulations across more than 15 U.S. states, we are shaping the future of transportation.The Simulation ML Infrastructure team is responsible for creating scalable AI/ML infrastructure that propels our Simulator team towards innovative, state-of-the-art simulations of realistic environments for the Waymo Driver's training and testing. By leveraging large foundation models trained on extensive datasets, we enhance the authenticity and control of our simulations, including realistic representations of vehicles, pedestrians, cyclists, roads, traffic control systems, and weather conditions.We are currently seeking a highly skilled Senior Machine Learning Infrastructure Engineer to spearhead the development of advanced AI/ML infrastructure for multi-billion parameter foundation models tailored for ML accelerator-friendly simulations. Your extensive knowledge in massive model scaling, ML accelerators, and distributed training will be vital in designing and optimizing our systems.

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:

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

Join our dynamic team at Spotify as a Staff Machine Learning Engineer, where you will be at the forefront of developing innovative AI solutions that enhance user experiences. In this role, you'll collaborate with cross-functional teams, leveraging your expertise in machine learning algorithms and data analysis to drive impactful projects.Your responsibilities will include designing and implementing machine learning models, optimizing algorithms for performance, and conducting research to stay ahead of industry trends. You will also mentor junior engineers, fostering a culture of knowledge sharing and continuous improvement.

Join Our TeamLatent Labs is on the lookout for a talented Machine Learning Research Engineer with extensive expertise in training and deploying large-scale generative models. In this pivotal role, you will oversee our high-performance computing infrastructure and drive our model serving initiatives. You will collaborate with a diverse team of machine learning experts, protein engineers, and biologists, all dedicated to transforming how we manipulate biological systems and develop innovative treatments for diseases.About Latent LabsAt Latent Labs, we are pioneers in creating advanced models that grasp the core principles of biology. Our team, which once co-developed DeepMind's groundbreaking AlphaFold and invented latent diffusion, is committed to scientific rigor and ambitious exploration. By joining us, you will work alongside some of the most brilliant minds in the fields of generative AI and biology, fostering a culture of collaboration and continuous learning between our London and San Francisco offices.We seek innovators who are passionate about solving complex problems and making a positive impact on the world. Be a part of our ambitious mission!

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.

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.

At Orbital Industries, we harness the power of artificial intelligence to revolutionize data center hardware, creating solutions that significantly surpass industry standards. Our innovative AI technology conducts atomic-level simulations of materials and evaluates millions of hardware configurations, identifying optimal designs that set new benchmarks in performance.Every deployment enhances our AI's capabilities, establishing a self-reinforcing cycle where improved models lead to superior hardware, ultimately enabling even more advanced AI solutions. We are not just participants in the AI revolution; we actively drive its momentum.While our primary focus is on data centers—which are characterized by urgent market demands and stringent specifications—the AI-driven development process we've perfected is applicable across any intricate physical system. Data centers serve as our initial proving ground, showcasing the vast potential of our technology.With operations in London, Canada, and the USA, we are building diverse teams in machine learning research, product development, mechanical engineering, and chemical engineering. If you're eager to explore the intersection of AI and material science, we want to hear from you.As a Staff Machine Learning Engineer, you will design and implement state-of-the-art AI systems for the multi-scale design of physical technologies. This role emphasizes the integration of world-class models that simulate both atomic motion and fluid dynamics in extensive data centers. You will collaborate closely with our scientists and engineers to co-design across these scales, leveraging advanced domain agents.In this position, you will establish high technical standards and guide projects from initial prototype stages to full production deployment. We seek a candidate who is passionate about craftsmanship, values continuous learning, and is dedicated to developing scalable systems. A humble approach and a genuine enthusiasm for applying AI to tackle significant global industrial challenges are essential.Key ResponsibilitiesEstablish and uphold high technical standards: Ensure excellence in code quality, system architecture, and machine learning practices through hands-on coding and technical evaluations.Design robust systems: Create well-engineered solutions that are scalable and maintain a balance between research pace and production needs.Drive technical decision-making: Lead decisions on model selection, training methodologies, and deployment strategies.

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.

About EDITEDEDITED is the premier AI-driven retail intelligence platform globally, empowering the most successful brands and retailers with the ability to make real-time decisions.By seamlessly connecting internal business data with external market insights, EDITED integrates intelligence into every retail decision. Our solutions help retailers enhance their margins, boost sales, and achieve superior business outcomes through AI-powered market and enterprise intelligence that propels automation.At EDITED, we cultivate a vibrant and inclusive culture where creativity flourishes, and collaboration is fundamental to our success. Our dynamic and supportive environment encourages team members to take initiative, innovate, and grow continuously. We prioritize diversity, transparency, and a shared commitment to excellence, fostering a workplace where every voice is valued, and contributions are celebrated.We understand that a healthy work-life balance is essential for driving innovation and success. Our flexible working arrangements—including hybrid working, flexible hours, and a work-from-anywhere policy—enable our team to perform at their best.

Why Join Faculty?Founded in 2014, Faculty believes that AI is the pivotal technology of our era. We have partnered with over 350 global clients to enhance their performance through human-centric AI. Our impact is tangible, as detailed here.We steer clear of fleeting trends. Our focus is on innovating, creating, and deploying responsible AI solutions that yield significant results. We offer clients extensive expertise across technical, product, and delivery domains, serving industries such as government, finance, retail, energy, life sciences, and defense.Our business and reputation are expanding rapidly. We seek individuals who share our intellectual curiosity and aim to build a positive legacy through technology.Join us in harnessing AI—an epoch-defining technology—where you will be empowered to envision and implement its most impactful applications.About the TeamThe process of delivering medical solutions involves complexity, cost, and risk. Faculty’s Life Sciences team is dedicated to developing AI solutions that enhance the research and commercialization of transformative therapies.We collaborate with leading pharmaceutical companies, academic research institutions, and MedTech startups to create solutions that address critical healthcare challenges, democratizing access to health for everyone.About the RoleAs a Machine Learning Engineer, you will deliver tailored, impactful AI solutions for our diverse clientele. You will play a crucial role in transitioning machine learning from theoretical frameworks to practical applications, contributing to robust software architecture and establishing best practices. Collaborating closely with clients and cross-functional teams, you will ensure the technical feasibility and timely delivery of high-quality, production-ready ML systems.Your Responsibilities:Developing and deploying production-grade ML software, tools, and infrastructure.Creating reusable, scalable solutions to expedite the delivery of ML systems.Working alongside engineers, data scientists, and commercial leaders to address significant client challenges.

Why Join Faculty?Founded in 2014, Faculty believes that artificial intelligence is the pivotal technology of our age. We have partnered with over 350 global clients, enhancing their performance through innovative, human-centric AI solutions. Discover our real-world impact here.At Faculty, we prioritize sustainable innovation over fleeting trends. Our focus is on developing and deploying responsible AI solutions that truly make a difference. Our expertise spans various sectors, including government, finance, retail, energy, life sciences, and defense, providing our clients with unparalleled technical, product, and delivery proficiency.As our reputation grows, we seek individuals who are intellectually curious and eager to leave a positive mark through technology.Join us in harnessing AI's transformative potential and be a part of a company that empowers you to realize its most impactful applications.About the TeamOur Defence team is dedicated to creating and implementing human-centered AI solutions that enhance our national defense capabilities. Collaborating closely with clients, we deliver ethical and advanced AI solutions for high-stakes scenarios, ensuring the stability of global powers crucial to our freedom.Due to the sensitive nature of our work, candidates must be eligible for UK Security Clearance (SC) and are expected to work on-site with clients for 2 to 4 days a week, which may involve travel across the UK. When not engaged with clients, you will have the flexibility to work from our London office or remotely within the UK.About the RoleAs a Senior Machine Learning Engineer, you will spearhead the development and deployment of advanced AI systems for a diverse range of clients. Your responsibilities will include designing, building, and deploying scalable, production-grade machine learning software and infrastructure that adhere to stringent operational and ethical standards.This role is ambitious and cross-functional, requiring a unique combination of technical acumen, engineering leadership, and strong client-facing abilities.

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.

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 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.