Senior Machine Learning Scientist

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.

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.

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.

Join Our Team as a Staff Machine Learning EngineerBecome an integral part of Deliveroo’s mission to revolutionize the shopping and dining experience with a focus on impact, innovation, and growth. Our talented Engineering teams tackle intricate technical challenges within a global, three-sided marketplace, developing and scaling systems that cater to millions of customers, riders, and partners daily.From advanced real-time logistics to robust infrastructure and marketplace optimization, we create and manage the technology that fuels Deliveroo’s expansive growth.We are seeking a Staff Machine Learning Engineer to join our dynamic London team (working in a hybrid model, 3 days in the office). In this pivotal role, you will design and construct intelligent decision-making systems that operate at a large scale, directly influencing the experiences of consumers, riders, and merchants.Explore our Engineering team and discover our motivations, work culture, and what you can expect as part of our community.Your ResponsibilitiesJoin the Consumer Pricing team to tackle complex pricing challenges at Deliveroo. We are advancing towards dynamic, personalized pricing strategies that take into account consumer behavior, loyalty programs, and real-time market conditions.Your daily tasks will include:Designing and developing high-performance machine learning and optimization systems that guide Deliveroo’s core decisions at scale.Leading the technical advancement of our pricing infrastructure, resolving architectural bottlenecks and integrating enhanced model inputs and decision variables.Creating algorithms to enhance real-time marketplace efficiency, including personalized elasticity models and delivery time forecasts.Collaborating closely with Product Managers and Data Scientists to convert complex business challenges into effective algorithmic solutions.Providing technical leadership across various product domains, identifying and prioritizing high-impact algorithmic enhancements.Mentoring and guiding fellow engineers, elevating technical standards and advancing our machine learning and optimization practices across the company.Qualifications for SuccessThe ideal candidate will possess strong expertise in several of the following areas, along with a desire to grow in others:

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.

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.

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 The Staff Machine Learning Engineer at AccuRx will work onsite in London (Shoreditch). The main focus is on creating and deploying machine learning models that help improve patient care and make healthcare workflows more efficient. This work aims to benefit both patients and healthcare professionals. What you will do Design, build, and deploy machine learning models for healthcare use cases Collaborate with engineering, product, and clinical teams to shape solutions Contribute to projects that influence patient outcomes and support healthcare providers

Join Our TeamLatent Labs is on the lookout for a talented Machine Learning Research Engineer with extensive expertise in training and deploying large-scale generative models. In this pivotal role, you will oversee our high-performance computing infrastructure and drive our model serving initiatives. You will collaborate with a diverse team of machine learning experts, protein engineers, and biologists, all dedicated to transforming how we manipulate biological systems and develop innovative treatments for diseases.About Latent LabsAt Latent Labs, we are pioneers in creating advanced models that grasp the core principles of biology. Our team, which once co-developed DeepMind's groundbreaking AlphaFold and invented latent diffusion, is committed to scientific rigor and ambitious exploration. By joining us, you will work alongside some of the most brilliant minds in the fields of generative AI and biology, fostering a culture of collaboration and continuous learning between our London and San Francisco offices.We seek innovators who are passionate about solving complex problems and making a positive impact on the world. Be a part of our ambitious mission!

Join our dynamic team at Spotify as a Staff Machine Learning Engineer, where you will be at the forefront of developing innovative AI solutions that enhance user experiences. In this role, you'll collaborate with cross-functional teams, leveraging your expertise in machine learning algorithms and data analysis to drive impactful projects.Your responsibilities will include designing and implementing machine learning models, optimizing algorithms for performance, and conducting research to stay ahead of industry trends. You will also mentor junior engineers, fostering a culture of knowledge sharing and continuous improvement.

Waymo, a pioneer in autonomous driving technology, is dedicated to becoming the world’s most trusted driver. Since its inception as the Google Self-Driving Car Project in 2009, Waymo has been at the forefront of innovation, developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility while significantly reducing the number of lives lost in traffic accidents. The Waymo Driver powers our fully autonomous ride-hailing service and is adaptable to various vehicle platforms and applications. With over ten million rider-only trips completed, fueled by our experience of autonomously driving over 100 million miles on public roads and tens of billions of miles in simulation across more than 15 U.S. states, we are transforming transportation.The Driver Understanding and Evaluation (DUE) team at Waymo is focused on creating comprehensive metrics to evaluate the Waymo Driver’s behavior in real-world scenarios. We are developing advanced technologies such as context and scene analysis to enhance our driving understanding, as well as augmenting real-world driving data to generate rare driving events. This includes building large-scale data infrastructures and improving components like agents and realistic simulators, which are pivotal for our technical strategies and methodologies in assessing the Waymo Driver's performance.The DUE Machine Learning team will develop and maintain scalable machine learning systems and simulation workflows, enhancing evaluation processes and developer onboarding experiences. By merging expert human insights with cutting-edge machine learning models, we will provide training and evaluation data across hundreds of metrics and components that define the Waymo Driver. We are seeking passionate researchers and software engineers eager to harness machine learning techniques to elevate the evaluation systems within our autonomous vehicles, driven by a relentless pursuit of performance improvement.This position reports to the Engineering Manager.

About EDITEDEDITED is the premier AI-driven retail intelligence platform globally, empowering the most successful brands and retailers with the ability to make real-time decisions.By seamlessly connecting internal business data with external market insights, EDITED integrates intelligence into every retail decision. Our solutions help retailers enhance their margins, boost sales, and achieve superior business outcomes through AI-powered market and enterprise intelligence that propels automation.At EDITED, we cultivate a vibrant and inclusive culture where creativity flourishes, and collaboration is fundamental to our success. Our dynamic and supportive environment encourages team members to take initiative, innovate, and grow continuously. We prioritize diversity, transparency, and a shared commitment to excellence, fostering a workplace where every voice is valued, and contributions are celebrated.We understand that a healthy work-life balance is essential for driving innovation and success. Our flexible working arrangements—including hybrid working, flexible hours, and a work-from-anywhere policy—enable our team to perform at their best.

Role overview Wise seeks a Staff Data Scientist specializing in Fraud Analysis to help advance fraud detection and prevention. This London-based role focuses on analyzing complex data to protect both the company and its customers. What you will do Apply advanced analytics and machine learning to identify and reduce fraudulent activities. Collaborate with teams across Wise to enhance fraud prevention systems. Produce insights that guide strategic decisions and strengthen safeguards for customers and the business.

At Orbital Materials, we harness the power of AI to revolutionize data center hardware, ensuring our products consistently outperform the competition. Our advanced AI simulates materials at the atomic level, allowing us to evaluate millions of hardware configurations in the time it would typically take to assess just hundreds. This innovative approach enables us to discover optimal designs that surpass traditional benchmarks, resulting in hardware specifications that competitors cannot match: 1 MW/rack, PUE As each deployment generates valuable field data, our AI models become increasingly sophisticated. This creates a virtuous cycle where improved models lead to better hardware, which in turn enhances our AI capabilities. We are not merely benefitting from AI advancements; we are actively driving its pace.Our focus on data centers is driven by an urgent market need and demanding specifications. However, the AI-accelerated development processes we've established—spanning materials discovery, hardware design, and manufacturing optimization—are applicable to any complex physical system. Data centers serve as our initial proof point, not the limit of our ambitions.With operations in London, Canada, and the USA, we are assembling teams across various domains including ML research, product development, mechanical engineering, and chemical engineering. If you're eager to work at the intersection of AI and physical sciences, we'd love to hear from you.As a Staff Machine Learning Engineer at Orbital, you will be instrumental in architecting sophisticated AI systems for the multi-scale design of physical technologies. By multi-scale, we mean that we create world-class foundational models capable of simulating everything from the microscopic motion of atoms to the macroscopic flow of liquids in 1GW data centers. You will collaborate across these diverse scales, leveraging the creativity of our scientists and engineers, augmented by premier domain agents.In this pivotal role, you will establish exceptionally high technical standards and lead projects from initial prototypes to full-scale production deployment. We seek individuals who possess a passion for craftsmanship, a commitment to continual learning, and a drive to build scalable systems. Additionally, we value a low-ego mindset and a genuine enthusiasm for leveraging AI to tackle significant global industrial technology challenges.

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 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!

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.

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.