CuspAI

<h2>About CuspAI </h2>CuspAI is the frontier AI company on a mission to solve the breakthrough materials needed to power human progress. While nature took billions of years to perfect molecules, we are harnessing AI to unlock trillion-dollar materials breakthroughs in months, not millennia. Our founding team is the most cited in the world, comprised of world-class researchers in AI, chemistry and engineering. We are working on some of the hardest and most important challenges including energy, clean water, the future of compute, and carbon capture, and this is just the start of what our 'search engine' for next-generation materials will unlock. We invite you to be part of a diverse, innovative team at the intersection of AI and materials science, working to create impactful partnerships that drive innovation, scalability, and industry collaboration. This work matters. Your work matters. We’re on the cusp of the on-demand materials era. Join us.<h2>The Role</h2>To scale our scientific intelligence and data curation capabilities, we are looking for three Research Engineers* to train and evaluate the foundation models behind our materials discovery platform: representation learning over crystal structures and properties, LLM fine-tuning and post-training for scientific tasks, and the evaluation and data work that makes those models useful. You will work in a small team where each person owns a model end to end, from data and experiment design through training at scale to integration. *Note that you would be joining as a ‘Member of Technical Staff’, but the job title above hopefully helps to explain the nature of this role.<h2> Your Impact</h2>You will be responsible for building and training specialised foundation models on terabytes of scientific data at massive scale, fundamentally enhancing our platform's multi-modal capabilities.The modalities span crystal structures, properties, text and images. Depending on your background you may lead on self-supervised representation learning, LLM fine-tuning and post-training (SFT, RL), or the evaluation suites that decide between them. <h2>What You Will Do</h2> Research and Model Training at Scale<ul><li>Design and run experiments: scaling studies, ablations and evaluations that settle which modelling choices survive.</li><li>Lead efforts in parallel training of multi-modal foundation models at scale (e.g. orchestrating parallel training across hundreds of GPUs and handling data in the order of Terabytes).</li><li>Apply strong software engineering best practices to ensure the systems are scalable, reliable, and maintainable.</li></ul><ul><li>Own the data curation and evaluation design for your models; these outlast the modelling decisions. </li></ul>Scientific Collaboration &amp; Integration<ul><li>Partner closely with our Chemists and Materials Scientists to integrate computational and experimental workflows into one seamless optimisation loop.</li><li>Be proactive in learning the technical vocabulary of materials science and experimental chemistry to facilitate meaningful interactions with domain experts.</li><li>Contribute to our mission by ensuring all system designs align with CuspAI's commitment to sustainability and world-changing challenges.</li></ul> <h2>Must Have Skills and Qualifications:</h2><ul><li>You are someone who gets excited about the opportunity to enable scientists to work on world changing challenges in this domain, with a personal interest in the potential applications of the technology that CuspAI is building.</li><li>Strong software engineering skills and a proven track record of building complex, high-performance systems at scale in a production or industrial environment.</li><li>Hands-on experience training or evaluating large models in a distributed setting. For senior candidates this means having led a multi-hundred-GPU training effort; for earlier-career candidates, having been a core contributor to one.</li><li>Depth in at least one of: large-scale vision or representation learning, LLM pre-training or post-training, reinforcement learning. We care more about one substantial, scale-y project than about breadth.</li><li>A deep interest in the connection between AI and materials science or chemistry, and a willingness to rapidly learn the scientific vocabulary of the discipline.</li><li>Master’s or PhD in CS, ML or a related quantitative field, or equivalent experience. We are hiring across levels: from strong early-career research engineers (typically 1 to 3 years at a frontier lab or equivalent) to senior and staff engineers who have led model programmes.</li><li>Experience with representation learning and computer vision, e.g. self-supervised or contrastive pre-training, learning embeddings, or building models that pull structured information out of images such as figures, plots and diagrams. </li></ul><h2>Bonus Points (But Not Critical):</h2><ul><li>RL for post-training (RLHF, GRPO-style methods) or RL in agentic settings.</li><li>Experience at a frontier lab or a team that ships models at scale.</li><li>Prior experience applying machine learning models specifically to problems in materials science, chemistry, or molecular informatics.</li><li>Exposure to multi-modal training (e.g. text, vision, etc.) and how to combine modalities in a meaningful way.</li></ul> <h2>Additional Considerations</h2>This role could be based in our Cambridge, London, Amsterdam or Berlin offices, with the expectation of being in the office three days per week. Additionally, there may be regular travel required to our other offices for collaboration and project oversight.<h2>What We Offer</h2><ul><li>A competitive salary: We value and reward impact and growth</li><li>Equity in CuspAI: You have a stake in the success of the company</li><li>Time off to stay fresh: 28 days holiday (DE, NL, UK) or 21 days holiday (JP, SG, US), in addition to local public holidays</li><li>‘Gold Standard’ parental leave: 26 weeks (primary caregiver) and 12 weeks (secondary caregiver) at full pay - we look after you and your family while we work on the most important materials discovery problems together</li><li>Professional development budget: We invest in your career development so you can stay up to date with the latest industry knowledge or add to your skills to increase impact and growth</li><li>Solve meaningful problems: See how your work has a direct impact on advancing materials science and solving sustainability and climate-related problems through the creation and application of bleeding-edge SOTA technology and revolutionary techniques</li><li>True interdisciplinary teamwork: Be part of a deeply collaborative environment bridging AI research, computational chemistry, and experimental science - work with world-class researchers and engineers who enjoy sharing knowledge and supporting each other</li></ul> Join us in shaping the future of materials with AI. Together, we can create groundbreaking solutions for a more sustainable world. CuspAI is an equal opportunities employer committed to building a diverse and inclusive workplace. We do not discriminate on the basis of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding), veteran status, or any other basis protected by applicable law. We actively encourage applications from all backgrounds and value the unique perspectives and contributions that diversity brings to our team. Please let us know if you require any specific adjustments during or after the interview process. We will do everything we can within reason to accommodate.

Research Engineer (Materials Foundation Models)

<h2>About CuspAI </h2>CuspAI is the frontier AI company on a mission to solve the breakthrough materials needed to power human progress. While nature took billions of years to perfect molecules, we are harnessing AI to unlock trillion-dollar materials breakthroughs in months, not millennia. Our founding team is the most cited in the world, comprised of world-class researchers in AI, chemistry and engineering. We are working on some of the hardest and most important challenges including energy, clean water, the future of compute, and carbon capture, and this is just the start of what our 'search engine' for next-generation materials will unlock. We invite you to be part of a diverse, innovative team at the intersection of AI and materials science, working to create impactful partnerships that drive innovation, scalability, and industry collaboration. This work matters. Your work matters. We’re on the cusp of the on-demand materials era. Join us.<h2>The Role</h2>Due to rapid growth in our core AI capabilities, we are seeking an experienced Applied AI/ML Engineer (Agents) to design and build the intelligent agents that power our autonomous materials discovery engine.<h2>Your Impact</h2>You will be instrumental in developing the "artificial brain" of our agentic materials discovery engine. This is responsible for orchestrating complex, closed-loop scientific workflows, autonomously making decisions, running simulations, and driving experimental campaigns to find breakthrough materials faster than ever before. Your work will directly accelerate CuspAI’s path to finding solutions for global sustainability challenges.<h2>What You Will Do</h2>Agentic systems<ul><li>Design the agentic framework that powers our platform to discover new materials. This includes spanning dynamic, multi-stage simulation workflows from literature-grounded hypothesis generation through to computational and experimental validation</li><li>Build the integration that connects agents to ML models, simulation engines, databases, and heterogeneous compute backends</li><li>Design pipelines that let agents autonomously plan, schedule, execute, and interpret computational tasks at scale and over long periods of time</li><li>Use expert annotations from the Chemistry team to drive targeted improvements in agent planning, retrieval, and decision-making</li><li>Create evaluations to measure the effectiveness of agents</li></ul>Experimental design<ul><li>Build agents that perform experimental design — applying Bayesian optimization, active learning, or related sequential decision-making methods to decide what to compute or measure next, and to balance exploration and exploitation across long-running discovery campaigns</li><li>Help close the loop between simulation and physical experiments so that outcomes become durable knowledge — feeding back into what agents know and how their models reason — compounding across campaigns.</li><li>Develop strategies for multi-fidelity and multi-objective decision-making, where agents must trade off cost, time, and uncertainty across simulations and physical experiments</li></ul>Interdisciplinary Collaboration<ul><li>Work closely with Chemists, Materials Scientists, and the rest of the Agent team to co-develop our core orchestration intelligence</li><li>Work on customer projects and implement the direct needs required for these projects</li></ul><h2>Must Have Skills and Qualifications:</h2><ul><li>You are someone who gets excited about the opportunity to enable scientists to work on world changing challenges in this domain, with a personal interest in the potential applications of the technology that CuspAI is building.</li><li>Proficiency in the modern ML ecosystem such as PyTorch or JAX, with experience taking ML-driven systems from prototype to production</li><li>Strong software engineering skills (building systems at scale in a production environment): testing, modular design, CI/CD, and scalable ML operations in production environments</li><li>If you have a PhD or Masters degree and 4-5 yrs industry experience this would be ideal, but we will also consider you if you have a PhD and slightly less experience in industry</li><li>You have a proactive builder mentality with a bias toward shipping and iteration</li><li>Willingness to learn about materials science, and in particular experimental chemistry - to learn the vocabulary of the discipline to meaningfully interact with other stakeholders</li><li>Experienced in LLM-assisted programming, knowing its strengths and weaknesses thoroughly.</li></ul><h2>Bonus Points (But Not Critical):</h2><ul><li>Experience applying ML models specifically for materials science, chemistry, or drug discovery applications</li><li>Experience with agentic frameworks and building LLM-powered applications</li><li>Experience with sequential decision-making methods — Bayesian optimization, active learning, bandits, or reinforcement learning — applied to real-world systems</li><li>Advanced agentic-reasoning techniques: planning models, self-improving systems, multi-tool agents, or RLHF/RLAIF workflows</li></ul><h2>Additional Considerations</h2>This role could be based in our Cambridge, London, Amsterdam or Berlin offices, with the expectation of being in the office three days per week. Additionally, there may be regular travel required to our other offices for collaboration and project oversight. Join us in shaping the future of materials with AI. Together, we can create groundbreaking solutions for a more sustainable world.<h2>What We Offer</h2><ul><li>A competitive salary: We value and reward impact and growth</li><li>Equity in CuspAI: You have a stake in the success of the company</li><li>Time off to stay fresh: 28 days holiday (DE, NL, UK) or 21 days holiday (JP, SG, US), in addition to local public holidays</li><li>‘Gold Standard’ parental leave: 26 weeks (primary caregiver) and 12 weeks (secondary caregiver) at full pay - we look after you and your family while we work on the most important materials discovery problems together</li><li>Professional development budget: We invest in your career development so you can stay up to date with the latest industry knowledge or add to your skills to increase impact and growth</li><li>Solve meaningful problems: See how your work has a direct impact on advancing materials science and solving sustainability and climate-related problems through the creation and application of bleeding-edge SOTA technology and revolutionary techniques</li><li>True interdisciplinary teamwork: Be part of a deeply collaborative environment bridging AI research, computational chemistry, and experimental science - work with world-class researchers and engineers who enjoy sharing knowledge and supporting each other</li></ul> Join us in shaping the future of materials with AI. Together, we can create groundbreaking solutions for a more sustainable world. CuspAI is an equal opportunities employer committed to building a diverse and inclusive workplace. We do not discriminate on the basis of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding), veteran status, or any other basis protected by applicable law. We actively encourage applications from all backgrounds and value the unique perspectives and contributions that diversity brings to our team. Please let us know if you require any specific adjustments during or after the interview process. We will do everything we can within reason to accommodate.

Applied AI/ML Engineer (Agents)

<h2>About CuspAI </h2>CuspAI is the frontier AI company on a mission to solve the breakthrough materials needed to power human progress. While nature took billions of years to perfect molecules, we are harnessing AI to unlock trillion-dollar materials breakthroughs in months, not millennia. Our founding team is the most cited in the world, comprised of world-class researchers in AI, chemistry and engineering. We are working on some of the hardest and most important challenges including energy, clean water, the future of compute, and carbon capture, and this is just the start of what our 'search engine' for next-generation materials will unlock. We invite you to be part of a diverse, innovative team at the intersection of AI and materials science, working to create impactful partnerships that drive innovation, scalability, and industry collaboration. This work matters. Your work matters. We’re on the cusp of the on-demand materials era. Join us.<h2>The Role</h2>As we grow, we are seeking a Data Engineer to play a crucial part in driving our research and development efforts forward. <h2>Your Impact</h2>As a Data Engineer you will be part of the new team building the infrastructure that underpins and acts as the critical bridge between raw chemical data and our machine learning models.Your main focus will be to build the pipeline infrastructure and tooling for data ingestion, moving towards self-serve setup for the scientific team members. You'll also be responsible for securing, collecting, cleaning, standardising, and tagging diverse chemical datasets to create high-quality training data for our ML researchers while working closely with our chemistry team to ensure scientific accuracy. <h2>What You Will Do </h2>Data Pipeline Development<ul><li>Design and build robust data pipelines for materials science datasets, experimental results, and computational chemistry outputs.</li><li>Develop processes to integrate diverse data sources including materials databases, literature, patent filings, and laboratory instruments.</li><li>Create automated workflows for processing crystallographic data, molecular structures, and materials properties (you don’t need to have direct domain experience - we can help bring you up to speed!).</li><li>Build scalable systems to handle high-throughput computational chemistry calculations and experimental data. </li></ul>Data Quality &amp; Standardisation<ul><li>Partner closely with scientists to implement frameworks to automate quality checks for crystal structure data, chemical compositions, and experimental measurements.</li><li>Build monitoring systems to ensure data integrity across all pipelines. </li></ul>Collaboration &amp; Integration<ul><li>You will also be working hand in hand with ML researchers to understand data requirements for model training and inference.</li><li>Integrate with laboratory automation systems and computational chemistry software.</li><li>Support real-time data needs for AI-driven materials discovery experiments. </li></ul><h2>Must Have Skills and Qualifications</h2><ul><li>You are someone who gets excited about the opportunity to enable scientists to work on world changing challenges in this domain, with a personal interest in the potential applications of the technology that Cusp is building.</li><li>You’re a builder of tools and infrastructure who enjoys making life as easy as possible for the teams, providing self-serve, reliable and scalable ingestion pipelines.</li><li>You have at least 3+ years experience in data engineering roles, preferably in scientific or research environments - you would be joining as a data engineering subject matter expert who can not only work autonomously but also provide guidance on best practice.</li><li>High level of proficiency in Python and databases with experience in large-scale data processing - as part of our engineering team you’ll be programming regularly, not just scripting.</li><li>You’re an advanced user of workflow orchestration tools (e.g. Airflow, Prefect, Dagster, Flyte or similar).</li><li>Solid experience with containerisation (Docker, Kubernetes) and CI/CD practices.</li></ul><ul><li>You have direct experience handling large/complex datasets and are interested in working with scientific packages.</li><li>You’re a fast learner when it comes to new tools/systems.</li><li>You enjoy (and have experience in) designing systems that scale with growing data volumes and user demands.</li><li>Understanding and appreciation of DevOps practices is also important.</li></ul><h2>Bonus Points (But Not Critical)</h2><ul><li>You’ve worked with data from scientific computing (simulations or experiments).</li><li>Knowledge of machine learning data requirements and MLOps practices, including pre-processing/processing as part of model training.</li><li>An academic background in Materials Science, Chemistry, Chemical Engineering, or related field.</li></ul>Even more bonus points if you have an understanding of crystallography, materials properties, and computational chemistry concepts!<h2>What We Offer</h2><ul><li>A competitive salary: We value and reward impact and growth</li><li>Equity in CuspAI: You have a stake in the success of the company</li><li>Time off to stay fresh: 28 days holiday (DE, NL, UK) or 21 days holiday (JP, SG, US), in addition to local public holidays</li><li>‘Gold Standard’ parental leave: 26 weeks (primary caregiver) and 12 weeks (secondary caregiver) at full pay - we look after you and your family while we work on the most important materials discovery problems together</li><li>Professional development budget: We invest in your career development so you can stay up to date with the latest industry knowledge or add to your skills to increase impact and growth</li><li>Solve meaningful problems: See how your work has a direct impact on advancing materials science and solving sustainability and climate-related problems through the creation and application of bleeding-edge SOTA technology and revolutionary techniques</li><li>True interdisciplinary teamwork: Be part of a deeply collaborative environment bridging AI research, computational chemistry, and experimental science - work with world-class researchers and engineers who enjoy sharing knowledge and supporting each other</li></ul> Join us in shaping the future of materials with AI. Together, we can create groundbreaking solutions for a more sustainable world. CuspAI is an equal opportunities employer committed to building a diverse and inclusive workplace. We do not discriminate on the basis of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding), veteran status, or any other basis protected by applicable law. We actively encourage applications from all backgrounds and value the unique perspectives and contributions that diversity brings to our team. Please let us know if you require any specific adjustments during or after the interview process. We will do everything we can within reason to accommodate.

CuspAI

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Research Engineer (Materials Foundation Models)

Applied AI/ML Engineer (Agents)

Data Engineer

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