Machine Learning Software Engineer - Research

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.

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

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.

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 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!

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 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.

We invite candidates to apply for the position that best aligns with their expertise. If we find a better fit for your profile, we will contact you about alternative opportunities. Position Overview: Conduct research utilizing statistical techniques, including time-series analysis, machine learning, and natural language processing to derive insights from data. Analyze extensive data sets employing advanced statistical and machine learning methodologies to uncover trading opportunities. Collaborate in developing statistical and machine learning tools to address complex data-related challenges across the organization. Typical Day: Engage in researching innovative statistical and machine learning techniques and exploring various datasets throughout the day. Present and discuss research findings with fellow researchers. Deploy and oversee models utilized for generating trading signals.

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.

Join latentlabs as a distinguished Machine Learning Researcher specializing in generative modeling. You will collaborate with a diverse team of machine learning experts, protein engineers, and biologists, all dedicated to revolutionizing biological control and disease treatment. Your primary focus will be to design innovative generative models aimed at creating new proteins that demonstrate functionality in wet lab assays.Who You AreExpert in Machine Learning Research. You possess substantial experience in generative modeling and have contributed to significant machine learning projects, as evidenced by your involvement in prominent open-source libraries, impactful product launches, or high-caliber publications at conferences such as NeurIPS, ICML, or ICLR.Skilled ML Developer. You produce robust, well-tested, and maintainable ML code. Your familiarity with version control and code review practices ensures high-quality development. You excel at rapid prototyping while also crafting polished production-ready code, with experience in running training and inference on cloud infrastructure.Data Engineering Proficient. You have a strong background in creating ML data pipelines for training and evaluating deep learning models. You’re skilled at analyzing raw data, creating effective dataset splits, and building scalable pipelines.Passionate About Model Performance. Your deep understanding of ML libraries, hardware interactions, and data optimization enables you to enhance the performance of deep learning models, focusing on training and inference speed and validation metrics.Driven and Inquisitive. You have a strong desire to effect positive change, whether for patients or customers. You adapt flexibly to diverse methodologies and are curious about challenges, no matter their scale. Your ability to thrive in a fast-paced environment allows you to achieve goals effectively.What Sets You ApartExperience in Computational Biology or Protein Design. You have engaged in ML-driven projects within the biological domain.Natural Sciences Background. Your foundation in natural sciences supports your work in machine learning applications.

At Orbital Industries, we harness the power of artificial intelligence to revolutionize data center hardware, setting new benchmarks in performance. Our innovative AI technology simulates materials at the atomic level and evaluates millions of hardware configurations far more rapidly than traditional methods, allowing us to uncover optimal designs that surpass industry standards.Each deployment generates valuable field data that continuously enhances our AI models. This iterative process leads to superior hardware, which in turn fuels more sophisticated AI capabilities. Our development cycle is a closed loop that tightens with every iteration, making us not just participants in AI evolution, but powerful catalysts for its acceleration.We focus on data centers as our initial market, given the urgent specifications and competitive landscape. However, our AI-driven methodologies—spanning materials discovery, hardware design, and manufacturing optimization—are versatile enough to apply to any intricate physical system. Data centers serve as our proof of concept, not our limiting factor.With teams located in London, Canada, and the USA, we're expanding our capabilities in machine learning research, product development, mechanical engineering, and chemical engineering. If you are eager to explore the intersection of AI and atomic science, we would love to connect with you.As a Senior Machine Learning Researcher at Orbital Industries, you will be responsible for designing cutting-edge AI systems for the multi-scale design of physical technologies. Our work encompasses creating world-class foundational models that simulate both atomic motion and liquid flow in 1GW data centers. You will collaborate across these different scales, leveraging the expertise of our scientists and engineers, enhanced by top-tier domain agents.In this role, you will establish high technical standards and guide projects from their inception to production deployment. We seek an individual who is passionate about craftsmanship, committed to continuous learning, and dedicated to developing scalable systems. A low-ego approach and a genuine enthusiasm for employing AI to tackle significant global industrial challenges are essential qualities we value.

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

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

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.

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 specifications: 1 MW/rack, PUE Every deployment contributes valuable field data that refines our AI models. Improved models yield superior hardware, and this cycle of continuous enhancement accelerates our advancements in AI. We are not merely observers of AI progress; we actively influence its trajectory.Our focus on data centers is driven by the urgent market demand and stringent specifications, but our AI-driven development process—covering materials discovery, hardware design, and manufacturing optimization—extends to any complex physical system. Data centers serve as our initial testing ground, not our limit.With operations in London, Canada, and the USA, we are expanding our teams across Machine Learning Research, Product Development, Mechanical Engineering, and Chemical Engineering. If you're eager to explore the intersection of AI and materials science, we want to connect with you.In the role of Staff Machine Learning Researcher, you will design and implement state-of-the-art AI systems for multi-scale physical technology design. Our multi-scale approach involves creating leading foundation models that simulate both the atomic motion of materials and the macroscopic fluid dynamics in 1GW data centers. You will facilitate cross-scale co-design, utilizing the expertise of our scientists and engineers, complemented by industry-leading domain agents.This position requires you to set high technical standards and lead projects from initial prototype stages to full production deployment. We seek a candidate who is passionate about craftsmanship, committed to continuous learning, and adept at building scalable systems. A collaborative spirit and a genuine enthusiasm for applying AI to tackle significant global industrial challenges are essential.

Join Synthesia, the premier AI video platform revolutionizing business communication, utilized by over 90% of Fortune 100 companies. Established in 2017 and headquartered in London, we proudly operate across Europe and the US, driving innovation in visual communication and enterprise skill development.As the landscape of AI evolves, our mission at Synthesia is to enhance how individuals and organizations communicate and learn, positioning ourselves at the forefront of the digital transformation.With our recent Series E funding of $200 million, we are valued at $4 billion, backed by over $530 million in funding from elite investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, as well as the founders of Stripe, Datadog, Miro, and Webflow.Role OverviewYou will play a vital role in developing our innovative Agentic AI Agents, overseeing the secure rollout of your features to our diverse customer base. This involves engaging in two-way communication using advanced conversational AI technology.Your responsibilities will encompass both user experience design and technical challenges, including infrastructure development and machine learning tasks, giving you the opportunity to work with cutting-edge LLMs.You will take full ownership of long-term projects, mastering the ability to decompose complex problems into manageable, iterative steps for delivery and validation.Collaborating closely with the product manager, you will be instrumental in shaping the commercial direction of the product, contributing to ideation and strategic problem-solving.Your role will also involve assessing the impact of your work through our established data pipelines and frameworks, allowing for adjustments based on commercial objectives.You will help steer the long-term vision of our team, ensuring we continuously develop our engineering capabilities to meet future challenges head-on.

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!

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 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 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