About Sylvera Sylvera empowers organizations to make informed investments in carbon and commodity markets. Our independent assessments of carbon project quality, market pricing, and supply signals, alongside our geospatial and carbon intensity data, provide clients with the vital insights needed for impactful climate action.Our diverse team of over 130 scientists, engineers, and market analysts operates across major cities including London, New York, São Paulo, Singapore, and Tokyo. We specialize in market intelligence, geospatial analytics, multi-scale lidar research, and policy analysis, partnering with governments to enhance transparency and rigor in carbon markets.With backing from over $96 million in investment from prominent firms like Fidelity, Balderton Capital, Index Ventures, and Insight Partners, we are trusted by Fortune 500 companies and major financial institutions globally.If you are passionate about climate science, enjoy tackling complex challenges, and wish to work with a dedicated team committed to our mission, we invite you to explore this opportunity.Role Overview ‍‍We are seeking a dedicated Applied Scientist – Forest Lidar & 3D ML to join our Earth Analytics (EA) team.Your primary focus will be to address a significant research challenge in a high-impact commercial context: the automation of tree segmentation from intricate terrestrial laser scanning (TLS) point clouds. Your work will be pivotal in enhancing Sylvera’s innovative Biomass Atlas product, which is increasingly utilized for carbon accounting within carbon markets. You will gain exclusive access to a premier ground-truth, labeled dataset of 3D forest point clouds sourced from global forests.Key Responsibilities:Designing, training, and implementing advanced 3D deep learning models (e.g., sparse convolutions, PointNet, TreeLearn, or similar architectures) for automating tree instance segmentation and Quantitative Structure Model (QSM) generation.Converting experimental machine learning research into reliable, reproducible code, collaborating closely with our production engineering team to deploy models at scale.

At Intercom, we are revolutionizing customer service through artificial intelligence, empowering businesses to deliver outstanding customer experiences.Our AI agent, Fin, stands as the most sophisticated customer service AI agent available, allowing companies to provide continuous, flawless customer support, ultimately enhancing customer interactions. Fin seamlessly integrates with our Helpdesk to form the Intercom Customer Service Suite—a comprehensive solution that offers AI-augmented assistance for more complex or high-touch inquiries that necessitate human intervention.Since our inception in 2011, Intercom has earned the trust of nearly 30,000 businesses worldwide and is setting a new benchmark in customer service. Guided by our core values, we consistently push boundaries, work with speed and intensity, and deliver exceptional value to our clients.What’s the Opportunity?The Machine Learning team at Intercom is tasked with defining innovative ML features, researching suitable algorithms and technologies, and quickly delivering initial prototypes to our customers.Our team is deeply product-focused, collaborating closely with Product and Design teams. Our dedicated ML product engineers enable rapid transitions to production, often launching beta versions just weeks after successful offline testing.We are passionate about harnessing machine learning technology, having productized everything from traditional supervised models to cutting-edge unsupervised clustering algorithms and novel transformer neural network applications. We rigorously evaluate the real customer impact of each model we deploy.What Will I Be Doing?Identifying opportunities where machine learning can add value for our customers.Defining the appropriate ML framing for product challenges.Collaborating with teammates and stakeholders from Product and Design.Conducting exploratory data analysis and research.Gaining a deep understanding of the problem areas.Researching and selecting the most suitable algorithms and tools.Being pragmatic while pushing the boundaries of innovation when necessary.Performing offline evaluations to validate algorithm effectiveness.Working alongside engineers to transition prototypes into production.Planning, measuring, and sharing insights to guide iterative development.Collaborating closely with the team and others to create exceptional ML products.

Role overview Trustpilot is hiring a Data Scientist for the Applied AI team in London. This position centers on Go-To-Market strategies, using data analytics and machine learning to support business growth. What you will do Apply advanced analytics and machine learning to guide business decisions Work with teams across the company to bring AI solutions into marketing efforts Help improve customer engagement and optimize marketing performance Location Based in London.

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.

Role overview The Trade Desk seeks a Staff Applied Scientist for its London office. The position centers on building advanced algorithms and machine learning models that enhance the digital advertising platform. Collaboration with both scientists and engineers is a key part of the role, all with the aim of improving how brands connect with their audiences. What you will do Develop and improve algorithms that support programmatic advertising solutions Apply machine learning methods to analyze and interpret large-scale data sets Work alongside a multidisciplinary team to advance the platform Offer scientific insight to projects that influence the direction of digital advertising Requirements Background in data science, applied science, or machine learning Strong skills in algorithm development Interest in the technical aspects of digital advertising Comfort working with diverse technical teams Location This role is based in London.

Isomorphic Labs is at the forefront of artificial intelligence, striving to unveil profound scientific insights, accelerate breakthroughs, and develop transformative medicines with the aim of eradicating all diseases.The future is unfolding—a future enriched by the remarkable capabilities of machine learning, where diseases are managed or cured through enhanced and expedited drug discovery.Join our interdisciplinary team, where your contributions will play a pivotal role in driving innovation and achieving our ambitious objectives, all within a collaborative and inspiring culture.The world we aspire to create begins today, with the culture we foster at Isomorphic Labs, and it starts with you.Research Scientist - Applied Large Language ModelsYour ImpactAs a Research Scientist specializing in Large Language Models (LLMs), you will be instrumental in leveraging cutting-edge technology across our research domains to revolutionize the drug discovery landscape.Working in a dynamic and creative environment, you will collaborate with leading researchers and engineers to envision, design, and develop state-of-the-art LLM applications that unlock new modeling capabilities and enhance predictive power—critical elements for the organization’s success.

About WheelyWheely is at the forefront of revolutionizing premium transportation across major cities in Europe, the US, and the Middle East. We integrate advanced technology with the art of five-star chauffeuring, providing an experience trusted by over 100,000 active riders and 1,200 corporate partners.As a profitable and rapidly growing scale-up, we have raised $43M and generated over $100M in annual revenue. With our recent expansion into New York City, we are accelerating our growth across the US and EMEA. If you are passionate about your craft and eager to help shape the next phase of our journey, we invite you to connect with us.We are looking for mid-level and senior Data Scientists / Machine Learning Engineers who will take ownership of the entire workflow, from ideation and research to production deployment.Join one of our specialized teams (Mapping, Matching, Pricing, or Supply) to tackle complex and high-impact challenges such as ETA prediction, routing, map matching, dynamic pricing, bipartite matching, driving style prediction, and LLM integration.

Wise seeks a Lead Machine Learning Engineer / Scientist based in London. This role centers on developing and refining machine learning models and algorithms that help drive data-informed decisions throughout the company. What you will do Build and enhance machine learning models to support Wise’s products and services. Collaborate with teams from various disciplines to deliver scalable, effective solutions. Apply advanced algorithms to improve decision-making and strengthen product offerings. Collaboration This position involves working closely with colleagues across the business, bringing together expertise from different areas to solve complex challenges and deliver impactful results.

Join Vortexa, a leader in the energy data analytics sector, as a Data Scientist specializing in production-grade machine learning. In this role, you will harness the power of advanced algorithms to process thousands of energy data points per second from diverse operational sources. Your expertise will be crucial in managing vast datasets while implementing sophisticated classification and anomaly detection models in real-time. You will maintain comprehensive data lineage and deliver actionable insights through high-performance platforms utilized by energy operators around the world.As a member of the Data Platform Team, you will oversee all machine learning operations across our extensive energy data ecosystem. Your work will span from raw sensor data from millions of energy assets to complex operational datasets, generating high-value predictions such as equipment failure detection, energy demand forecasting, operational anomaly identification, predictive maintenance scheduling, and system optimization recommendations.We pride ourselves on developing a robust suite of statistical and machine learning models that provide the most precise and actionable insights into energy operations. Our models are continuously validated by in-house energy analysts and traders, ensuring the reliability of our predictions. You will play a key role in designing and building ML infrastructure and applications that enhance the design, deployment, and monitoring of ML pipelines and models.Collaborating closely with software engineers, fellow data scientists, and energy analysts, you will help bridge the gap between research experiments and production energy systems, ensuring operational uptime and fault tolerance of our ML platform.

Join our innovative team at Helical as a Senior Computational Scientist, where your expertise in computational biology and machine learning will directly contribute to transformative drug discovery processes. You will play a pivotal role in bridging the gap between our foundational models and real-world applications, guiding model evaluations and practical use cases that address pressing challenges in drug development and translational research.As a respected senior individual contributor, you will report to the Head of Computational Biology, with ample opportunities for career advancement into management roles as our team expands. You will collaborate closely with our research team, providing mentorship to junior scientists and working in tandem with Product and Business Development to translate advanced biological concepts and machine learning techniques into impactful solutions for our clients.

Role overview ASOS Ltd. seeks an Applied Scientist for its Technology department in London. The focus is on applying advanced data analytics and machine learning to enhance customer experience and streamline internal operations. Key responsibilities Design and build algorithms, predictive models, and analytical tools in partnership with teams across the business. Use data-driven methods to support technology initiatives and advance strategic objectives at ASOS. Contribute to new solutions that have a measurable effect on customer service and operational efficiency. Collaboration This position works closely with colleagues from different disciplines to ensure technical solutions support the company's wider goals.

Intercom is an innovative AI Customer Service company dedicated to empowering businesses to deliver exceptional customer experiences.Our state-of-the-art AI agent, Fin, is recognized as the leading customer service AI solution available. It enables businesses to provide consistent, high-quality customer service, thereby enhancing their overall customer experience. Fin can seamlessly integrate with our Helpdesk to form the comprehensive Intercom Customer Service Suite, which offers AI-enhanced support for more complex queries that necessitate human intervention.Founded in 2011 and trusted by nearly 30,000 businesses worldwide, Intercom is redefining the customer service landscape. Guided by our core values, we continuously challenge the status quo, act with urgency, and strive to deliver remarkable value to our clients.What is the Opportunity?Our Machine Learning team at Intercom is pivotal in identifying and developing new ML features, exploring suitable algorithms and technologies, and swiftly delivering initial prototypes to our customers.We are a highly product-focused team, collaborating closely with our Product and Design partners. The dedicated ML product engineers on our team enable us to expedite our transition to production, often launching beta versions just weeks after successful offline testing.We are deeply passionate about harnessing machine learning technology, having productized a range from traditional supervised models to state-of-the-art unsupervised clustering algorithms and innovative applications of transformer neural networks. We rigorously test and evaluate the tangible customer impact of each model we deploy.What Will I Be Doing?Actively participate in recruitment, mentoring, and career development initiatives for fellow engineers.Elevate technical standards, performance metrics, reliability, and operational excellence.Pinpoint opportunities where ML can deliver significant value to our customers.Collaborate with team members and Product and Design stakeholders to define the appropriate ML framework for product challenges.Conduct exploratory data analysis and research to gain a deep understanding of the problem domain.Investigate and select suitable algorithms and tools, balancing practicality with cutting-edge innovation where necessary.Execute offline evaluations to validate algorithm efficacy.Collaborate with engineers to transition prototypes to production.Plan, measure, and disseminate insights to guide iterative improvements.

Role overview asos is seeking a Senior Machine Learning Scientist with a focus on Personalisation to join the London team. This position centers on building and enhancing machine learning models that influence how users experience the asos platform. What you will do Design and develop machine learning models to personalise the shopping experience for asos customers. Collaborate with data scientists, engineers, and product teams to create and refine algorithms that connect users with relevant products. Use data-driven approaches to increase user engagement and help customers discover items that match their preferences. Support the ongoing improvement of asos’s recommendation systems so customers can find what they need more easily. Collaboration This role sits within the data science team and works with cross-functional partners across asos. The work directly shapes the customer journey and the effectiveness of personalised recommendations on the platform.

About NevisNevis is pioneering the first-ever AI-driven wealth management platform, recently surpassing $50 billion in assets under management and projected to exceed $100 billion by year-end.Backed by prominent investors, Nevis has successfully secured $40 million in funding from Sequoia Capital, ICONIQ, and Ribbit, positioning itself as one of Europe’s most well-funded and rapidly expanding Series A startups.The RoleWe are on the lookout for an innovative and passionate Applied AI Engineer to join our dynamic team at Nevis. In this critical role, you will influence the development of our cutting-edge AI wealthtech product by creating LLM-driven automation solutions to tackle essential challenges faced by our corporate clients.You will engage with state-of-the-art LLM models, partnering with industry-leading vendors to enhance our product’s reasoning capabilities and achieve superior quality in our models’ outputs.Working alongside a distinguished team of engineers and product creators, including the ex-Head of AI at Revolut, you will have a unique opportunity to make a significant impact in one of the world’s largest industries.What You’ll DoDesign and develop LLM and ML-powered features for the Nevis platform.Collaborate with engineers and product teams to transition new AI capabilities from concept to production.Establish best practices for AI development, testing, observability, and reliability.Continuously assess and enhance AI product performance and reasoning accuracy.Work in tandem with product and design teams to prototype and refine new AI features.Stay abreast of advancements in Generative AI, including agentic systems and context engineering.Who You AreHands-on experience with LLMs.Demonstrated ability to solve real-world challenges using AI/ML.Strong statistical and data analysis skills.A STEM degree from a leading university.A passion for transformative AI technologies.A product-oriented mindset focused on practical solutions.

Join our team at physicsx as a Senior AI Engineer - Applied and be at the forefront of artificial intelligence innovation. This role involves leveraging cutting-edge technologies to develop AI solutions that address real-world challenges. You will collaborate with a talented team of engineers and researchers, contributing to projects that push the boundaries of AI applications.

Join datatonic as a Senior Machine Learning Engineer and be a pivotal part of our innovative team focused on transforming data into actionable insights. In this role, you will leverage your expertise in machine learning to develop and enhance algorithms, contribute to data-driven solutions, and collaborate with cross-functional teams to push the boundaries of data analytics.

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 datatonic as a Machine Learning Engineer and be part of a dynamic team dedicated to leveraging data to drive intelligent decision-making. You will design and implement machine learning models, optimize algorithms, and collaborate with cross-functional teams to deliver innovative solutions.

Join Trainline as the Head of Machine Learning Engineering, where you'll lead our innovative machine learning initiatives. In this pivotal role, you will spearhead the development and implementation of advanced ML solutions that enhance our customer experience and optimize our operations.