Research Engineer in Machine Learning - Reinforcement Learning

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.

At Google DeepMind, we prioritize diversity in experience, knowledge, backgrounds, and perspectives, leveraging these attributes to create remarkable impact. We are dedicated to providing equal employment opportunities regardless of sex, race, religion, belief, ethnic or national origin, disability, age, citizenship, marital status, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or any other condition protected by applicable law. If you have a disability or additional needs that require accommodation, please feel free to reach out to us.SnapshotWe seek talented Research Scientists to advance fundamental research and technology in Artificial Intelligence, as part of our interdisciplinary and collaborative Reinforcement Learning team.About UsDeepMind’s RL team is a cohesive and collaborative group of scientists and engineers, led by Tom Schaul. We address large-scale research challenges in reinforcement learning, designing, refining, and scaling RL algorithms to yield significant scientific and product impact. Over the past decade, our RL team has been pivotal in developing innovations such as DQN, AlphaGo, Rainbow, AlphaZero, MuZero, AlphaStar, AlphaProof, and Gemini. Join us in creating the next groundbreaking advancement!The RoleAs a Research Scientist, you will leverage your machine learning expertise and technical skills to innovate, spearhead research projects, and apply findings to impactful challenges. You will be responsible for implementing code, conducting experiments, owning results from start to finish, communicating findings effectively, and collaborating with fellow team members to empower others.Your work may involve:Initiating and pursuing novel research directions by proposing and testing hypotheses.Implementing algorithmic ideas and executing comprehensive experiments, including setup, execution, analysis, and iteration.Sharing your expertise and insights with other researchers.Building or enhancing infrastructure to support scalable research.Designing evaluations and ablations that address real questions and influence perspectives.Meticulously analyzing results, including debugging and failure analysis.Effectively communicating through visualizations, write-ups, and publication-ready narratives and figures.Contributing to a culture of first-principles thinking, high standards, and constructive feedback.Our projects encompass a broad spectrum of state-of-the-art machine learning and AI domains, including large language models, distributed machine learning, and more.

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.

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.

Join Our Innovative Team as a Machine Learning ResearcherAt Wintermute, we are on the forefront of digital asset trading, leveraging cutting-edge technology to provide unparalleled liquidity and OTC solutions across the cryptocurrency landscape. As a technology unicorn founded in 2017, we are a leading player in algorithmic trading, committed to supporting high-profile blockchain projects and ushering traditional financial institutions into the exciting world of crypto. Our venture arm also invests in early-stage DeFi initiatives, fostering innovation in the blockchain space.Our culture merges the rigor of high-frequency trading with the innovative spirit of tech startups, creating an environment that champions both technological excellence and entrepreneurial ambition. We believe in the transformative potential of blockchain technology, maintaining a long-term vision for the digital asset market while prioritizing compliance and innovation.Your Role and ResponsibilitiesAs a Machine Learning Researcher, you will harness your expertise in applied deep learning to develop robust alpha signal generation pipelines. Your work will encompass everything from data ingestion and feature engineering to model training and deployment, all in close collaboration with our dynamic trading and infrastructure teams.

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

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.

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.

About WheelyWheely is revolutionizing premium transportation across major cities in Europe, the US, and the Middle East. We integrate state-of-the-art technology with the art of five-star chauffeuring to provide an experience trusted by over 100,000 active riders and 1,200 corporate accounts.As a profitable and rapidly growing scale-up with $43 million raised and over $100 million in annual revenue, we have recently launched in New York City and are swiftly expanding throughout the US and EMEA. If you take pride in your expertise and wish to help shape the next phase of our growth, we invite you to connect with us.We are seeking Associate Data Scientists with a foundation in Operations Research. You will oversee the entire process—from ideation and research to production deployment.You will be part of either our Pricing or Matching team, collaborating with fellow Data Scientists and engineers to tackle challenging, high-stakes problems such as dynamic pricing and bipartite matching.

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 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.

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.

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.

Become a Catalyst for Change at Axon.At Axon, we are committed to safeguarding lives and enhancing public safety through innovative technology. As pioneers in the field, we tackle critical issues surrounding safety and justice with our comprehensive ecosystem of devices and cloud-based software solutions. Our collaborative culture thrives on open communication and diverse perspectives, both from our customers and within our teams.Working at Axon is not just a job; it's a chance to make a tangible difference. Here, you will take initiative and make a real impact while growing personally and professionally in a fast-paced, meaningful environment.Your RoleWe are looking for adept and forward-thinking Machine Learning Scientists to enhance our AI team, focusing on applications of AI, particularly in Large Language Models (LLM) and Computer Vision across Cloud, Devices, and Robotics. As an integral part of our research and development initiatives, you will significantly contribute to advancing cutting-edge technologies in LLMs, Multimodal Large Language Models (MLLMs), Computer Vision, and Generative AI for law enforcement applications and more. You will work collaboratively with multidisciplinary teams to innovate, develop, and implement advanced LLM, MLLM, and CV models, enabling intelligent reasoning and perception of multimodal data.

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

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.