Machine Learning Researcher at Jane Street | London

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.

We invite you to apply only for the position that aligns best with your skills and experience. Should our team determine you are a better fit for another opportunity, we will reach out accordingly. Position Overview:Conduct research and implement strategies within the firm’s automated trading systems.Utilize advanced statistical methods to analyze large data sets and uncover trading opportunities.Gain a comprehensive understanding of the market structures of various exchanges and asset classes. A Day in the Life of a Quant Researcher:Focus primarily on research and the implementation of trading ideas throughout the day.Prior to market opening, ensure all necessary data and processes are prepared for the trading day.During market hours, monitor the performance and behavior of strategies as needed.

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 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

IMC Trading is seeking skilled quantitative researchers to craft advanced high to mid-frequency delta one trading strategies and predictive models for the Equities markets. If you are passionate about leveraging Machine Learning in trading to unlock substantial execution advantages and collaborating to elevate our firm to the forefront of the trading industry, then this opportunity is tailored for you. With a rich history of competitive advantages in market access, global presence, options expertise, and low latency, IMC has significantly benefited from the rapid advancements in Machine Learning. Our focus is on tackling some of the most compelling and transformative challenges in the trading landscape. At IMC, we believe in teamwork, open idea sharing, and collaboration across various disciplines, desks, and offices to drive success.

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

Join Our Team as a Quantitative ResearcherAt Jane Street, we are seeking talented Quantitative Researchers to develop advanced models, strategies, and systems for pricing and trading financial instruments. Your expertise in experimental design, dataset generation, time series analysis, feature engineering, and model building will be pivotal in harnessing financial datasets. Collaborate with a dynamic team of experts who will challenge your ideas and refine your methodologies.Our collaborative environment places researchers, engineers, and traders in close proximity, allowing for seamless teamwork in training models, architecting systems, and executing trading strategies. We handle vast amounts of data and leverage an expansive GPU cluster with tens of thousands of high-performance GPUs. Daily tasks may involve deep analysis of market data, fine-tuning hyperparameters, enhancing distributed training performance, or understanding how our models perform in live trading.We embrace a diverse range of statistical and machine learning techniques, from linear models to deep learning, tailoring our approach to meet the unique challenges we face. The most successful researchers are those who possess a deep curiosity about how their work contributes to our overarching trading operations and adapt their insights into actionable strategies.

About the Role Jane Street is seeking enthusiastic Quantitative Researchers to join our dynamic team. In this role, you will collaborate closely with seasoned researchers to develop sophisticated models, strategies, and systems aimed at pricing and trading financial instruments. You will gain valuable insights into experiment design, dataset generation, time series analysis, feature engineering, and model building tailored for financial datasets. Our unique environment fosters collaboration between researchers, engineers, and traders, allowing for seamless interaction as we train models, architect systems, and execute trading strategies. With access to petabytes of data, a robust computing cluster featuring hundreds of thousands of cores, and an expanding GPU cluster housing tens of thousands of high-performance GPUs, you will engage in a wide range of activities—from analyzing market data and optimizing hyperparameters to debugging distributed training performance and evaluating our models' trading behavior in real-time. At Jane Street, we embrace diverse modeling approaches, prioritizing the application of various statistical and machine learning techniques, from linear models to deep learning, depending on the challenge at hand. Our most successful researchers possess a keen curiosity about how their contributions integrate into our broader trading operations and how to translate their findings into actionable strategies.

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.

Teza Technologies is actively seeking a highly skilled Senior Quantitative Researcher to become an integral part of our Options stream. This position calls for exceptional analytical capabilities, a steadfast dedication to excellence, and a fervor for identifying hidden patterns within data sets. If you are motivated by intellectual challenges and excel in tackling intricate problems, this role provides an extraordinary opportunity to advance your career.Our team cherishes determination, precision, and the capacity for both critical and creative thinking. Although the work is rigorous, the rewards are substantial, impacting your contributions and facilitating your growth in our collaborative, high-performance environment. We value autonomy and offer the freedom to develop cutting-edge algorithms in finance while emphasizing the vital aspect of effective communication.LocationLondon, UK (Hybrid mode with a requirement of 3 days in-office)Key ResponsibilitiesSpearhead the research and development of systematic options trading strategies across both US and global markets.Utilize advanced options pricing models, volatility surface modeling, and risk-neutral frameworks to generate alpha.Perform rigorous backtesting, stress testing, and statistical validation of strategies.Collaborate with technologists to translate research into production-ready trading systems with robust execution.Refine portfolio construction and risk management frameworks for options books.Contribute to the advancement of Teza’s options research platform, infusing innovation into live strategies.Mentor junior researchers and drive the continuous enhancement of research practices, infrastructure, and tools.Basic RequirementsDegree in Physics, Mathematics, Computer Science, Engineering, or another technical discipline.Strong mathematical skills in statistics, linear algebra, optimization, etc.A minimum of 4 years of quantitative research or trading experience in systematic trading.Extensive expertise in options, including volatility surface and derivatives pricing methods.Proficient programming skills in Python, with experience managing large, complex datasets.Solid understanding of risk management principles in derivatives trading.Ability to collaborate effectively across research and technology 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.

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.

Join M3 USA as an Associate Director of Quantitative Research, where you will play a pivotal role in leading cutting-edge market research initiatives in the EU. This position demands a strategic mindset and a keen analytical eye to drive impactful insights that empower our clients. You will collaborate with a diverse team of professionals and engage with stakeholders across various sectors, ensuring that our research methodologies remain at the forefront of industry standards.

Role Overview Fasanara Capital is seeking a Quantitative Researcher in London. This position focuses on applying advanced analytical methods to support investment strategies and strengthen data-driven decisions. The role involves close collaboration with the investment team to analyze market trends and build predictive models. What You Will Do Apply quantitative techniques to research financial markets and identify patterns Develop and refine predictive models to inform investment decisions Work alongside investment professionals to translate research into actionable strategies Contribute to the team’s understanding of market dynamics with rigorous analysis Location This role is based in London, England, United Kingdom.

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!

At Jump Trading Group, we are dedicated to pioneering world-class research in the financial sector. We empower the brightest minds in Mathematics, Physics, and Computer Science to explore scientific frontiers, surpass them, and harness cutting-edge research to innovate within global financial markets. Our culture fosters constant innovation, encouraging fearlessness, creativity, intellectual honesty, and a competitive spirit. We believe in collaborative success, unlocking unique individual talents through teamwork and mutual respect. At Jump, our research outcomes extend beyond superior risk-adjusted returns; we design, develop, and implement technologies that reshape industries, fund startups across various sectors, and collaborate with leading global research institutions and universities to address complex challenges.The quantitative trading teams at Jump Trading delve into the intricacies of global markets, striving to comprehend the complexities of diverse traded products and exchanges. They utilize their exceptional statistical analysis and data mining expertise, applying research findings to forecast trends and create profitable predictive trading models.

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.

Fasanara Digital, the cryptocurrency division of Fasanara Capital, has been at the forefront of digital asset investment for the past seven years. As a specialized alternative asset manager with over 14 years of experience, we adopt a rigorous quantitative approach to investing in crypto assets, aiming for exceptional risk-adjusted returns. Our diverse and sophisticated investment strategies leverage market inefficiencies, encompassing various techniques from market making to cross-exchange arbitrage.Our CultureAt Fasanara, we champion a meritocratic environment where individuals are recognized for their contributions and excellence. Our collaborative and entrepreneurial atmosphere is free from the constraints of bureaucracy, fostering trust and teamwork. We set high ambitions, work diligently, and uphold the highest standards of excellence, building our firm around exceptional talent.Position OverviewWe are looking for a Mid-Frequency Quantitative Researcher to spearhead the design, development, and deployment of systematic trading strategies within the digital asset market. This role will also support portfolio management for our multi-strategy book. You will be responsible for the entire research lifecycle, from idea generation and signal construction to implementation, monitoring, and continuous optimization, collaborating closely with execution and infrastructure teams.ResponsibilitiesConduct thorough research to develop and validate high-quality quantitative trading signals for the cryptocurrency markets.Lead the complete strategy development lifecycle, from hypothesis generation through to live deployment.Monitor live trading performance, assess risk exposures, and ensure strategy robustness.Continuously improve and refine existing models based on performance metrics and market dynamics.Create dashboards and analytics to facilitate monitoring and analysis of the Mid-Frequency strategy portfolio.Maintain clear documentation of research methodologies, findings, and enhancements.Effectively communicate insights, risks, and updates on strategies to internal stakeholders.