Senior Machine Learning Researcher at Longshot Systems | London

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

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

At Longshot Systems, we develop cutting-edge platforms for sports betting analytics and trading.We are currently seeking experienced Machine Learning Engineers to join our modeling engineering team. In this role, you will collaborate closely with our quantitative research teams to transform prototype trading models into robust, production-ready systems. You will be responsible for designing and building the tooling, frameworks, and data engineering necessary to support strategy research and development, while also architecting high-level designs of the strategy software to minimize trading latency and ensure scalability. Our ML stack is primarily Python-based, incorporating modern ML libraries and tools such as Polars, Ray, and Plotly.The ideal candidate will possess a solid software engineering background, with extensive experience in high-performance computing topics such as multi-threading, networking, profiling, and optimization. Proficiency with the NumPy/SciPy stack is essential, along with experience in performance optimization tools like C++ and Numba. Familiarity with common ML algorithms and techniques is advantageous but not mandatory.As a hybrid working company, we require team members to work in our London (Farringdon) office on Thursdays, while offering flexibility for remote work on other days. Our standard working hours are from 10 am to 6 pm UK time, Monday to Friday, but we encourage flexible schedules to help our team meet their objectives.Interview Process:Introductory Call (30 mins) - Discuss your background and interestsFirst Technical Interview (30 mins) - Live code review and pair programmingSecond Technical Interview (60 mins) - In-depth technical questionsFull Assessment Day (10:30 am to 5 pm) - A programming exercise reflective of actual team tasks

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

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

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 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.

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.

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.

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

Why Join Faculty?Founded in 2014, Faculty believes that artificial intelligence is the 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.

ASOS seeks a Machine Learning Engineer in London to focus on recommendation systems. The main responsibility involves developing and refining models that deliver personalized product suggestions to customers. Key responsibilities Design and implement machine learning models that improve the relevance of product recommendations. Translate data insights into practical updates for recommendation algorithms, working alongside team members. Contribute to projects aimed at enhancing the user experience through smarter, more tailored suggestions. Collaboration This role involves partnering with colleagues in data science and engineering to share expertise and strengthen the performance of ASOS’s recommendation systems.

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 Canva, our mission is to empower individuals to unleash their creativity through design. We are innovating AI technology that not only feels intuitive but also creates meaningful impacts for millions, enabling everyone to design with confidence. We are seeking a Senior Research Scientist passionate about reinforcement learning, agentic systems, and mixture of experts (MoE) models to advance our capabilities in reasoning, tool utilization, latency, and reliability.About the TeamOur team delves into multimodal agentic architectures, establishing robust training and evaluation frameworks. We collaborate closely with product and platform teams to transform groundbreaking research into engaging product features. As a pioneering post-training team, we are dedicated to developing advanced multimodal agentic systems. We cover a wide array of topics, including multimodal modeling, post-training strategies, and agent design.About the RoleIn this role, you will influence research directions and engage in hands-on initiatives across the agent stack—from reward design and policy optimization to planning, memory management, tool orchestration, dataset construction, and the innovation of post-training methodologies. You will create meticulously designed experiments, iterate rapidly, and derive reliable conclusions, all while ensuring that research translates into safe, high-quality product experiences.Key ResponsibilitiesDesign and develop agent systems focused on planning, multimodal tool usage, retrieval, innovative training methods, and modeling experiments for real-world applications in design, vision, and language.Implement scalable post-training and reinforcement learning solutions across distributed systems (using PyTorch), optimizing data loaders, telemetry, and stable training of MoE architectures while ensuring reproducibility.Contribute to the reinforcement learning and agentic systems research agenda that aligns with Canva’s product vision; quickly identify and prioritize high-impact projects.Create reward models and learning loops, including RLHF/RLAIF, preference modeling, DPO/IPO-style objectives, offline/online RL, and curriculum learning.Develop simulation tasks that expose failure modes (planning errors, tool-use weaknesses, hallucinations, unsafe actions) and establish measurable targets for improvement.Lead rigorous evaluations for agents, focusing on task success, reliability, latency, safety, and regression testing. Set up offline suites and conduct online A/B testing; favor straightforward experiments that yield generalizable results.Collaborate closely with product, design, safety, and platform teams to successfully integrate research findings into reliable product features.

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.