Staff Machine Learning Researcher at Orbital | London

At Orbital Materials, we leverage advanced AI technologies to engineer data center hardware that surpasses industry standards. Our AI capabilities simulate materials at the atomic level and evaluate millions of hardware configurations within a fraction of the time traditional methods require. This innovative approach leads to hardware with unmatched specific…

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.

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:

Embark on an exciting journey with us as we aim to transform real estate transactions into a seamless, swift, and intelligent process. The real estate market, being the largest asset class globally, still relies heavily on outdated and manual legal procedures. Legal professionals find themselves wading through tedious documents, while clients expect quicker and more transparent due diligence. Enter Orbital Copilot, our AI-powered assistant tailored for commercial real estate law. Created in collaboration with experienced real estate lawyers, it enhances complex due diligence processes by up to 70%, all while maintaining legal-grade accuracy. With a recent infusion of $60 million in Series B funding, we are poised for rapid expansion in the UK and US markets. Leading firms like Goodwin and BCLP trust us to eliminate redundant tasks, empowering legal teams to concentrate on delivering expert legal advice, exceptional client service, and closing deals more efficiently. Joining Orbital means becoming part of a dynamic team that is reshaping the future of real estate transactions—where speed, collaboration, and the ability to make a significant impact from day one are paramount.Your RoleAs a Senior Software Engineer, you will create innovative tools that revolutionize the transfer of the world’s largest asset class. We are shifting property transactions from manual document reviews to an automated AI solution that operates with the mindset of a real estate lawyer.Your contribution will not be limited to executing builds; you will leverage your expertise to guide product development and lay the groundwork for our next phase of growth, offering you real influence over our creations.Key ResponsibilitiesDevelop and deploy production software, transforming concepts into dependable customer-facing features.Collaborate with a close-knit team of engineers to design and implement new functionalities.Utilize AI coding agents to generate, iterate, and refine high-quality production code.Engage with a technology stack that typically includes TypeScript, React, PostgreSQL, and Python, while reviewing and guiding code produced by AI agents.Contribute to technical design and architecture decisions.

Join us on our quest to revolutionize real estate transactions by making them smarter, faster, and seamless. Real estate represents the largest asset class globally, yet the underlying legal processes and tools are often outdated, manual, and lacking investment. Legal professionals are burdened with reviewing lengthy documents meticulously while clients insist on quicker, more transparent due diligence. Enter Orbital Copilot, our AI-powered assistant designed specifically for commercial real estate law. Developed in collaboration with experienced real estate attorneys, it accelerates intricate due diligence processes by up to 70%, all while ensuring legal-grade accuracy. With a recent successful raise of $60 million in Series B funding, we are poised to expand our footprint in the UK and US markets. Leading firms like Goodwin and BCLP trust us to eliminate tedious tasks, allowing legal teams to concentrate on their core expertise: exercising astute legal judgment, delivering exceptional client service, and closing deals more efficiently. At Orbital, you will be part of a dynamic team reshaping the real estate transaction landscape—working swiftly, collaboratively, and empowered to create a meaningful impact from day one.Key Responsibilities: Design AI-driven products where smart systems are essential, enabling teams to accelerate their work and tackle significant challenges. Take ownership of the entire product development cycle, from concept to deployment, transforming ideas into tangible products for our users. Test cutting-edge AI models and translate innovative capabilities into actionable, production-ready applications. Rapidly prototype and validate concepts, confidently coding, testing solutions, and launching early iterations of products. Drive product strategy by collaborating closely with engineers and users to uncover opportunities and address real workflow issues. Continuously refine our product development approach by leveraging AI tools, rapid testing, and contemporary methodologies.Desired Qualifications: A genuine passion for creating products that significantly enhance how people work. A strong interest in AI and a motivation to explore its potential for unlocking new product experiences.‍ A product manager with a background in technology and a proven track record of successfully launching products.

Join us on our mission to revolutionize real estate transactions, making them smarter, faster, and more seamless. The real estate sector is the largest asset class globally, yet its legal processes are still slow, manual, and underfunded. Lawyers often find themselves sifting through complex documents and fragmented information, all while clients demand quicker and more transparent due diligence. That’s where we come in. Orbital Copilot is an AI-powered assistant crafted specifically for commercial real estate law. In collaboration with experienced real estate lawyers, we’ve designed a tool that accelerates intricate due diligence processes by up to 70%, ensuring legal-grade accuracy. We have recently secured a $60 million Series B funding round to expedite our expansion in the UK and US markets. Our trusted partners include leading law firms such as Goodwin and BCLP, who rely on us to eliminate mundane tasks, allowing their legal teams to focus on delivering exceptional client service and expediting deal closures. At Orbital, you will be part of a dynamic team that is redefining the future of real estate transactions—embracing speed, collaboration, and empowerment from day one.Role Overview We are seeking our second Site Reliability Engineer to enhance our platform and reliability initiatives. This position presents an exciting chance to design, implement, and oversee our infrastructure, CI/CD pipelines, and production operations from scratch. You will have the autonomy to shape our technological framework, establish best practices, and develop scalable systems that will lay the groundwork for our future engineering endeavors. If you thrive in a startup culture and enjoy the intersection of software engineering, operations, and infrastructure, we invite you to connect with us.Your Responsibilities Include: ‍ ‍Infrastructure Management:Design and maintain a robust, cloud-based infrastructure on Azure.Develop and manage infrastructure as code (IaC) using tools like Terraform.Take ownership of our system’s reliability and scalability, establishing a solid foundation for our engineering environment.Container Deployment and Orchestration:Manage deployment and orchestration of containerized applications, ensuring efficient performance and reliability.

Join Our Innovative Team as a Machine Learning ResearcherAt Wintermute, we are on the forefront of digital asset trading, leveraging cutting-edge technology to provide unparalleled liquidity and OTC solutions across the cryptocurrency landscape. As a technology unicorn founded in 2017, we are a leading player in algorithmic trading, committed to supporting high-profile blockchain projects and ushering traditional financial institutions into the exciting world of crypto. Our venture arm also invests in early-stage DeFi initiatives, fostering innovation in the blockchain space.Our culture merges the rigor of high-frequency trading with the innovative spirit of tech startups, creating an environment that champions both technological excellence and entrepreneurial ambition. We believe in the transformative potential of blockchain technology, maintaining a long-term vision for the digital asset market while prioritizing compliance and innovation.Your Role and ResponsibilitiesAs a Machine Learning Researcher, you will harness your expertise in applied deep learning to develop robust alpha signal generation pipelines. Your work will encompass everything from data ingestion and feature engineering to model training and deployment, all in close collaboration with our dynamic trading and infrastructure teams.

PhysicsX is looking for a Machine Learning Software Engineer to join its research division in London. This position centers on developing new machine learning solutions in collaboration with researchers and engineers. Role overview The work involves applying advanced algorithms and data analysis techniques to address complex challenges spanning several fields. The team values creative problem-solving and technical depth. Collaboration Expect to work closely with colleagues from diverse backgrounds, combining expertise to create practical and innovative solutions. The environment encourages sharing ideas and learning from each other. Location This role is based in London, United Kingdom.

Anthropic seeks a Research Engineer specializing in Machine Learning, with a focus on Reinforcement Learning (RL Velocity), for its London office. This role supports ongoing AI research and contributes to building advanced machine learning systems. Key responsibilities Work alongside researchers and engineers to solve complex reinforcement learning problems Participate in designing and developing new machine learning models and systems Shape solutions that directly influence Anthropic’s research objectives Collaboration and team environment Join a team of skilled colleagues dedicated to AI advancement. Team members regularly exchange ideas, review each other's work, and support one another to create effective solutions.

About the Position We are seeking intelligent and inquisitive individuals to enhance our dynamic Machine Learning team at Jane Street. This role offers the opportunity to develop cutting-edge deep learning models that underpin our trading strategies, utilizing our expansive computing cluster equipped with tens of thousands of high-performance GPUs. The trading environment presents unique challenges, including large-scale models and nonstationary datasets within a competitive multi-agent landscape, prompting innovative solutions. At Jane Street, our researchers, engineers, and traders collaborate closely, sharing knowledge and expertise just a few feet apart. Your day may involve analyzing market data, optimizing hyperparameters, diagnosing distributed training performance, or exploring our models' behaviors in live trading scenarios. Your extensive knowledge of the machine learning domain and familiarity with diverse methodologies—ranging from LLMs, image recognition systems, RL agents, recommendation frameworks, to classical ML techniques—will be invaluable in advancing ML at Jane Street. You will play a crucial role in training models for our next-generation deep learning trading strategies and developing the insights necessary to navigate new markets and challenges. Furthermore, you will be involved in the recruitment of new team members, attending industry conferences, and sharing your expertise with colleagues, all of which are considered significant contributions to our mission.

At Orbital Industries, we harness the power of artificial intelligence to create cutting-edge data center hardware that surpasses industry standards. Our innovative AI technology simulates materials at the atomic level, allowing us to evaluate millions of hardware configurations in the time it takes traditional methods to assess only hundreds. This leads to the development of optimal designs that are unmatched in performance.Each deployment generates valuable field data that continuously enhances our AI models. This cycle of improvement means that as our models become more sophisticated, so does the hardware we produce, enabling even more advanced AI capabilities. We are not just passive participants in the evolution of AI; we are actively driving its advancement.Our focus on data centers is driven by the urgency of the market and the demanding specifications of our clients. However, the AI-enhanced development processes we have established—spanning materials discovery, hardware design, and manufacturing optimization—are applicable to any intricate physical system. Data centers serve as our initial proving ground, not the limit of our capabilities.With operations in London, Canada, and the USA, we are assembling teams across multiple disciplines, including machine learning research, product development, mechanical engineering, and chemical engineering. If you are passionate about where AI intersects with material science, we want to connect with you.Role OverviewAs the Engineering Manager at Orbital, you will be responsible for the design and implementation of our internal AI software platform, known as Curie. You will oversee the development of features that integrate materials, engineering, and manufacturing into a cohesive system for our AI agents. Your leadership will set high engineering standards, guide projects from initial prototype to production deployment, and manage a talented software team.We seek individuals who have a passion for craftsmanship, a commitment to continuous learning, and a drive to build scalable systems.

About UsEstablished in the United States in 2022 and now operating from London, UK, Recraft is an innovative AI platform tailored for designers, illustrators, and marketers, setting a new benchmark in image generation excellence.Our cutting-edge tool empowers creators to swiftly generate and refine original images, vector art, illustrations, icons, and 3D graphics using advanced AI technology. With over 3 million users in 200 countries, our community has produced hundreds of millions of images with Recraft, and we are just beginning our journey.Become part of a world filled with professional opportunities, contribute to large-scale projects, and be a pioneer in the creative industry’s future. We are dedicated to making Recraft a vital tool for every designer, striving to set the industry standard. Our mission focuses on ensuring that creators maintain complete control over their creative processes with AI, offering them innovative tools to transform their ideas into reality.If you have a passion for pushing the limits of AI technology, we would love to have you join our team!

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 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!

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

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.

physicsx is seeking a Staff Machine Learning Software Engineer to join its Research team in London. This position centers on building advanced algorithms and machine learning solutions to drive forward ambitious research initiatives. Role overview The main focus is on designing and implementing machine learning models that push the boundaries of current technology. Projects will involve exploring new methods and supporting research efforts that aim to solve complex problems. Location This role is based in London, United Kingdom. What you will do Develop and refine machine learning algorithms for research applications Collaborate with researchers to support innovative projects Work on solutions intended to advance the capabilities of existing technology

Isomorphic Labs is pioneering the application of advanced AI technologies to unlock profound scientific insights, expedite breakthroughs, and develop transformative medicines with a vision to eradicate all diseases.The future is on the horizon, made possible by the remarkable capabilities of machine learning. We envision a world where diseases are effectively managed or eliminated through accelerated and enhanced drug discovery.Join our interdisciplinary team to spearhead groundbreaking innovations and play a pivotal role in our mission to achieve ambitious health-related goals, all while contributing to a vibrant and collaborative workplace culture.The future we aspire to is being shaped today. It begins with our culture at Isomorphic Labs. It starts with you.About Isomorphic LabsFounded in 2021, Isomorphic Labs (IsoLabs) strives to enhance human health by building upon the Nobel Prize-winning AlphaFold system. Our diverse team of experts in drug discovery and machine learning has developed groundbreaking predictive and generative AI models that accelerate scientific discovery at an unprecedented pace.Our name reflects our belief in the inherent symmetry between biology and information science. By leveraging AI's robust capabilities, we can model complex biological processes to design innovative molecules, predict drug performance, and develop novel treatments for some of the world's most challenging diseases.Our state-of-the-art drug design engine integrates AI models capable of addressing various therapeutic areas and drug modalities. We are dedicated to continuously innovating model architectures and creating cutting-edge solutions to advance rational drug design.With each significant advancement, we are progressing towards the promise of digital biology, moving closer to our ambitious mission of ultimately solving all diseases through the power of AI.

Join Jane Street as a Senior Weather Analyst and Machine Learning Researcher, where you will leverage advanced analytical techniques and cutting-edge machine learning algorithms to interpret and predict weather patterns. Your expertise will contribute to our innovative approach to trading strategies and risk management based on meteorological data.