Senior Software Engineer - Machine Learning

Join Cambridge Mobile Telematics (CMT), the largest telematics service provider globally, dedicated to enhancing road safety and improving driver behavior. Our AI-driven platform, DriveWell Fusion®, integrates sensor data from numerous IoT devices, including smartphones, connected vehicles, and dashcams, to provide actionable insights for auto insurers, automakers, and public safety organizations. With headquarters in Cambridge, MA, and offices across the globe, we are committed to making a difference for millions of drivers every day.As a Principal Machine Learning Engineer on the innovative DriveWell Atlas team, you will lead the charge in developing cutting-edge AI systems leveraging telematics data. You will spearhead projects that involve the design, pre-training, fine-tuning, and deployment of novel foundation models aimed at revolutionizing risk assessment, driver engagement, and claims processing. This role demands a profound understanding of contemporary AI methodologies, machine learning, and sensor data analysis, offering the chance to construct a pioneering large language model from petabyte-scale datasets.We seek a collaborative and inventive Principal Machine Learning Engineer who is driven by a passion for making roads safer and improving driver capabilities.

Join Cambridge Mobile Telematics (CMT), the premier telematics service provider dedicated to enhancing safety on roads worldwide. Our AI-powered platform, DriveWell Fusion®, integrates sensor data from millions of IoT devices—such as smartphones, connected vehicles, and dashcams—along with contextual data to provide comprehensive insights into vehicle and driver behavior. Our solutions empower auto insurers, automakers, commercial mobility entities, and public sector organizations to enhance risk assessment, improve safety, streamline claims, and promote driver improvement initiatives. With a global presence, including offices in Budapest, Chennai, Seattle, Tokyo, and Zagreb, CMT is committed to safeguarding tens of millions of drivers every day.We are currently seeking a dynamic and innovative Director of ML Engineering, Foundation Models. This pivotal role involves leading the development of our Telematics Foundation Model and its associated variants. You will champion the AI Modeling and AI Operations teams, ensuring a balance between meeting immediate customer needs and advancing long-term research and development goals. Your expertise in machine learning will translate cutting-edge advancements into practical applications across our platform, products, and client solutions.

ABOUT PIONEERING INTELLIGENCE Pioneering Intelligence is a forward-thinking initiative that builds upon Flagship Pioneering's rich history of establishing groundbreaking scientific and computational enterprises. By leveraging cutting-edge advancements in artificial intelligence, machine learning, and data science, we aim to accelerate fundamental research and cultivate a dynamic portfolio of AI-first companies. As an integral part of Flagship's unique model that intertwines science, entrepreneurship, and investment, we transform revolutionary concepts into impactful companies, enhancing AI innovations that contribute to human health, sustainability, and more. THE ROLE We are on the lookout for a Principal Scientist specializing in Embedded Machine Learning and Computational Methods to spearhead various AI/ML and computational initiatives across early-stage ventures within our company origination framework. Your responsibilities will include defining and executing practical AI strategies, overseeing the development of methodologies and platforms (including systems design, drug design, molecular modeling, systems biology, protein design, and LLM-based workflows), and ensuring a high standard of rigor in model development, benchmarking, scaling, and reporting. You will also manage cross-functional teams as necessary, influence the strategic direction of our initiatives, and represent Pioneering Intelligence to venture teams and external collaborators. The ideal candidate is a self-motivated individual with a diverse skill set, capable of transitioning seamlessly from protein design to mass spectrometry or docking pipelines, and then creating LLM-based agents to streamline scientific workflows.

ABOUT PIONEERING INTELLIGENCEPioneering Intelligence extends Flagship Pioneering's tradition of launching innovative scientific and computational initiatives. By leveraging the latest advancements in AI, machine learning, and data analytics, we aim to expedite fundamental research and build a diverse portfolio of AI-first companies. As a key player in Flagship's integrated approach to science, entrepreneurship, and investment, we transform groundbreaking concepts into transformative enterprises that enhance AI innovations in human health, sustainability, and more.THE ROLEWe are on the lookout for a Principal Scientist specializing in Embedded Machine Learning and Computational Techniques to spearhead various AI/ML and computational initiatives across early-stage ventures in our company origination process. You will be responsible for defining and executing practical AI strategies, overseeing the development of methodologies and platforms such as systems design, drug design, molecular modeling, systems biology, protein design, and LLM-driven workflows while ensuring the utmost rigor in model development, benchmarking, scaling, and reporting. You will manage cross-functional contributors as necessary, influence the strategic direction of the company, and represent Pioneering Intelligence to venture teams and external partners. The ideal candidate is a proactive, deep thinker who can seamlessly transition between protein design one week and mass spectrometry or docking pipelines the next, while also developing LLM-based agents to automate scientific workflows.

ABOUT PIONEERING INTELLIGENCE Pioneering Intelligence continues the legacy of Flagship Pioneering by creating innovative scientific and computational ventures. Utilizing advancements in AI, machine learning, and data analytics, our mission is to expedite fundamental research and establish a diverse portfolio of AI-first companies. We integrate science, entrepreneurship, and capital to transform groundbreaking concepts into impactful companies, furthering AI advancements in human health, sustainability, and more. THE ROLE We are on the lookout for a Principal Scientist in Embedded Machine Learning/Computational to spearhead multiple AI/ML and computational projects within early-stage ventures as part of Flagship’s origination process. Your responsibilities will include defining and executing effective AI strategies, leading method and platform advancements (such as systems design, drug design, molecular modeling, systems biology, protein design, and LLM/agentic workflows), and ensuring excellence in model development, benchmarking, scaling, and reporting. You'll collaborate with cross-functional teams, shape the direction of the company, and represent Pioneering Intelligence to both venture teams and external partners. The ideal candidate is a proactive deep diver, capable of transitioning from protein design to mass spectrometry or docking pipelines, and then developing LLM-based agents to streamline scientific workflows.

Location: Cambridge, MA (Eastern Time / UTC -4). Relocation support is available. Remote work may be considered for candidates based outside Massachusetts.Start date: ASAPLanguages: English (required) Pragmatike is an AI startup founded by MIT CSAIL researchers, recognized by GTM Capital as a Top 10 GenAI company. The team develops advanced AI systems with a focus on real-world applications. Role overview The Principal Machine Learning Operations Engineer shapes the architecture and scaling of Pragmatike’s machine learning infrastructure. This senior position leads the design, implementation, and optimization of production AI systems, overseeing the full lifecycle from model training and evaluation to deployment, monitoring, and ongoing improvement. Collaboration is central in this role. The Principal ML Ops Engineer works closely with AI researchers, GPU systems engineers, backend developers, and product teams. The main focus is building reliable, efficient, and automated ML platforms to support large-scale AI deployments. Key responsibilities Architect, build, and improve the end-to-end ML Ops pipeline, including training, fine-tuning, evaluation, rollout, and monitoring. Design and maintain infrastructure for model deployment, version control, reproducibility, and orchestration across both cloud and on-premises GPU clusters. Optimize distributed systems for computational efficiency, covering Kubernetes, autoscaling, caching, GPU allocation, and checkpointing workflows. Establish observability for ML systems by monitoring model drift, performance, throughput, reliability, and operational costs. Automate workflows for dataset curation, labeling, feature engineering, evaluation, and CI/CD for ML models. Collaborate with researchers to bring models into production and improve training and inference pipelines. Set internal ML Ops standards, best practices, and develop tools that support cross-team collaboration. Mentor engineers and provide architectural guidance across the AI platform. Requirements Extensive hands-on experience designing and operating production ML systems at scale, ideally at the Staff or Principal level. Deep knowledge of ML Ops, distributed systems, and cloud infrastructure.

Join Cambridge Mobile Telematics (CMT), the largest telematics service provider globally, dedicated to enhancing road safety for all drivers. Our innovative AI-driven platform, DriveWell Fusion®, aggregates data from millions of IoT devices—including smartphones, proprietary Tags, connected vehicles, and dashcams—fusing it with contextual information to provide a comprehensive view of driver and vehicle behavior. Our insights are utilized by auto insurers, automobile manufacturers, commercial mobility companies, and public sector entities to enhance risk assessment, safety protocols, claims processing, and driver improvement initiatives. With our headquarters in Cambridge, MA, and offices in Budapest, Chennai, Seattle, Tokyo, and Zagreb, we safeguard millions of drivers worldwide every day.As a Principal Machine Learning Engineer at CMT, you will craft algorithms that model the physical phenomena associated with vehicle and human movements as captured by mobile sensors and IoT devices. Your expertise will help solve complex real-world challenges and drive innovative solutions through exploratory data analysis on intricate, high-dimensional datasets. Leveraging your knowledge in statistics, machine learning, deep learning, signal processing, physics, programming, and data modeling, you will spearhead Data Science projects, independently create new solutions to meet CMT’s goals, and contribute to company-wide prototype development and product enhancements.If you are a collaborative, customer-focused, and inventive Principal Machine Learning Engineer eager to contribute to safer roads and better driving practices, we welcome your application!

Collaboration Fuels Innovation. Join Roku in Transforming TelevisionAs the leading TV streaming platform in the U.S., Canada, and Mexico, Roku aims to power every television globally. We pioneered the streaming revolution, and our mission is to connect the entire TV ecosystem. We empower viewers with access to their favorite content, assist content creators in reaching vast audiences, and offer advertisers unparalleled engagement tools.From day one at Roku, your contributions will be recognized and valued. In our rapidly growing public company, you won’t just observe; you will play a vital role in enhancing the experience for millions of TV streamers across the globe while gaining invaluable experience across various fields. About the TeamThe Advanced Development team at Roku is at the forefront of innovation, creating the next generation of intelligent and generative media systems. We explore concepts that are years ahead of production, crafting foundational technologies that will redefine content understanding, creation, and personalization across millions of Roku devices.This unique environment is comprised of a PhD-level, interdisciplinary team that merges machine learning research, software engineering, and DevOps. Our experts possess not only deep technical knowledge but also a broad creative vision, challenging the status quo, embracing uncertainty, and building unprecedented solutions. Our culture is collaborative, low-ego, and driven by ownership, trust, and curiosity.We seek an Applied Scientist with a robust foundation in mathematics, machine learning, and computer science, complemented by experience in cloud engineering, DevOps, and computer vision — someone who excels at the intersection of research and production.

Join the Team at GraphcoreAt Graphcore, we are at the forefront of revolutionizing AI computation. Our team of experts in semiconductors, software, and artificial intelligence is committed to developing an advanced AI compute stack that encompasses everything from silicon to datacenter infrastructure.As a proud member of the SoftBank Group, we are supported by significant long-term investment, enabling us to drive crucial technology within the rapidly expanding SoftBank AI ecosystem.To address the immense opportunities within the AI landscape, we are seeking to expand our teams globally. We welcome the brightest minds to tackle the most challenging problems, ensuring that every team member has an opportunity to influence our company, our products, and the future of AI.

Your Impact at Lila As a Machine Learning Engineer on the Physical Sciences team, you will play a pivotal role in developing and managing comprehensive, scalable machine learning workflows. These workflows will address a wide range of scientific challenges in materials science, chemistry, and physical sciences. Your contributions will be instrumental in advancing research initiatives focused on cutting-edge algorithms, driving towards the establishment of scientific superintelligence to tackle today’s most significant challenges in physical sciences. What You Will Build Design, implement, and sustain end-to-end ML pipelines, encompassing data ingestion, feature engineering, model training, evaluation, deployment, and monitoring. Productionize models and services while ensuring robust testing, observability, and documentation in collaboration with cross-functional software teams; develop CI/CD workflows and automated evaluations to facilitate safe and frequent releases. Work closely with domain scientists and platform engineers to translate research insights into high-performing, scalable systems. Participate in technical design reviews, establish coding standards, and mentor colleagues on best practices. What You’ll Need to Succeed BS, MS, or PhD in Computer Science, Engineering, or a related quantitative field, or equivalent industry experience. A solid foundation in Python software engineering, including testing, packaging, and typing; experience with machine learning frameworks such as PyTorch and Hugging Face. Experience deploying ML services in cloud-based environments (FastAPI/GRPC, containers, orchestration, cloud infrastructure). Hands-on experience with deploying models in production systems (LLMs, multimodal models, databases, RAG) along with strong debugging and profiling skills. Effective communication and collaboration in cross-functional settings. Bonus Points For Familiarity with scientific or engineering domains (materials, chemistry, physics) and related data formats/benchmarks. Experience in GPU optimization (CUDA, Triton, compilation, distributed training). Previous contributions to open-source ML or scientific software. Experience with workflow orchestration, data provenance, or large-scale computing environments. About Lila Lila Sciences stands as the pioneering platform for scientific superintelligence, offering an autonomous laboratory dedicated to life sciences, chemistry, and materials science. We are at the forefront of a new era of limitless discovery, harnessing AI to revolutionize research and innovation in these fields.

Collaboration Drives Innovation. Join Roku in Transforming Television ViewingRoku stands as the premier TV streaming platform across the U.S., Canada, and Mexico, aiming to revolutionize how people experience television on a global scale. As pioneers in TV streaming, our mission is to create a platform that connects the entire television ecosystem. We bridge the gap between consumers and their favorite content, empower content creators to reach and monetize vast audiences, and equip advertisers with unique tools to engage effectively with viewers.At Roku, your contributions are vital from day one. As a rapidly expanding public company, we value proactive engagement from all employees. This is your chance to create delightful experiences for millions of TV streamers worldwide while gaining invaluable experience across diverse disciplines. About the TeamWith over 70 million active accounts, Roku leads the way in the TV streaming industry across North America. Our commitment to machine learning and innovative recommendation systems is central to our ongoing success. We enable users to access an extensive library of content, including movies, series, news, sports, music, and channels from around the globe. Role OverviewIn this role, you will deepen our understanding of queries, content, and user behavior through machine learning. Your work will be pivotal in enhancing user satisfaction throughout their search journey. Tackling these challenges is at the heart of our mission to improve customer experience.

Join Cambridge Mobile Telematics (CMT), the leading provider of telematics solutions worldwide, dedicated to enhancing road safety for drivers everywhere. Our innovative AI-driven platform, DriveWell Fusion®, aggregates sensor information from millions of IoT devices—including smartphones, connected vehicles, dashcams, and proprietary Tags—along with contextual data to deliver an integrated perspective on vehicle and driver behavior. Our insights empower auto insurers, automakers, commercial mobility firms, and government entities to enhance risk assessment, safety protocols, claims management, and driver improvement initiatives. With headquarters in Cambridge, MA and additional offices in Budapest, Chennai, Seattle, Tokyo, and Zagreb, we protect and monitor millions of drivers globally every day.CMT is seeking a talented and experienced Senior Software Engineer to contribute to the development and scalability of our on-device Machine Learning systems within the Mobile SDK. This pivotal team is responsible for the core C/C++ runtime that enables real-time sensor data processing and machine learning across a multitude of mobile devices. Our platform facilitates swift updates and deployment of driving behavior algorithms while ensuring optimal performance, battery efficiency, and operational accuracy.If you are a collaborative, customer-focused, and innovative individual eager to help us improve road safety by enhancing driver behavior, we invite you to apply!

Join us at the Toyota Research Institute (TRI) as we strive to enhance the quality of human life through innovative technologies. Our mission is to create groundbreaking tools that enrich human experiences. To spearhead this transformative evolution in mobility, we've assembled a stellar team that is pushing the boundaries in artificial intelligence, robotics, driving, and material sciences.The TeamWithin TRI's Energy and Materials division, the Future Factory team is dedicated to pioneering advanced tools and methodologies that drive flexibility and efficiency in Toyota's product design and manufacturing processes. Our goal is to expedite the journey towards an emissions-free future. We are developing comprehensive AI systems capable of reasoning through the creation of physical objects — from initial design concepts to the assembly of actual components — and building the necessary infrastructure to train and evaluate these systems on a large scale.The OpportunityWe are seeking a Research Scientist to help us build intelligent systems for physical assembly. This role is an excellent fit for recent PhD graduates with a proven track record in implementation and a deep curiosity about the manufacturing process.As a member of our research team, you will design and implement learning pipelines from the ground up, conduct experiments to assess various architectural, data, and algorithmic alternatives, and influence the application of modern machine learning to the challenges of robotic assembly. Your work will intersect policy learning, reinforcement learning, and physical reasoning, allowing you to explore the integration of large language models and agentic infrastructure in solving real-world manufacturing challenges.

About Graphcore At Graphcore, we are pioneering the future of AI computation. Our team consists of semiconductor, software, and AI specialists with extensive experience in creating a complete AI compute stack—from silicon and software to infrastructure at datacenter scale. As a proud member of the SoftBank Group, we are supported by significant long-term investments, allowing us to deliver vital technology to the rapidly expanding SoftBank AI ecosystem. To seize the immense and exciting opportunities in AI, Graphcore is actively expanding its teams globally, uniting the brightest minds to tackle the most challenging problems in an environment where everyone can significantly impact the company, its products, and the future of artificial intelligence. Job Summary In the role of Senior Machine Learning Engineer within the Applied AI team at Graphcore, you will play a crucial part in advancing AI technology by developing and optimizing AI models specifically designed for our specialized hardware. You will engage with large-scale systems where performance is paramount to the success of our initiatives. Collaborating closely with both the Software Development and Research teams, you will be instrumental in identifying innovative opportunities that set Graphcore’s technology apart. We are looking for engineers with robust technical skills and a deep understanding of large-scale AI model implementation, eager to make a meaningful impact in this fast-evolving field. The Team The Applied AI team's mission is to serve as advocates for our customers. We continually strive to understand the latest AI models, applications, and software to ensure that Graphcore’s technology integrates seamlessly with the AI ecosystem and operates efficiently at scale. Our responsibilities include building reference applications, optimizing key software libraries (including kernel efficiency on our hardware), and collaborating with the Research team to develop and publish innovative ideas across domains such as efficient computation, model scaling, and distributed training and inference of AI models across various modalities and applications. If you are passionate about advancing the next generation of AI models on cutting-edge hardware, we would love to hear from you!

Your Impact at Lila As an ML Research Scientist specializing in Multimodal Data Extraction, you will play a pivotal role in advancing Lila's mission of achieving scientific superintelligence. Your work will focus on the development of foundational models capable of autonomously reading, interpreting, and organizing scientific knowledge from diverse formats such as text, images, and experimental data in the physical sciences. Your research will contribute to the unification of global scientific data into a machine-readable format, enhancing reasoning, prediction, and autonomous discovery within materials science and chemistry. What You Will Be Building Innovate and create AI systems that effectively extract and organize knowledge from a variety of scientific resources. Design and optimize large language models, multimodal models, and specialized architectures for accurate and interpretable data extraction. Develop scalable solutions for managing unstructured and heterogeneous scientific data, integrating various formats including text, tables, and visuals. Collaborate with subject matter experts to ensure that the extracted data aligns with real-world research workflows. Publish impactful research that propels the field of multimodal understanding and AI-driven knowledge extraction forward.

Are you passionate about advancing the field of machine learning? Join our team at Altos Labs as a Machine Learning Scientist or Senior Machine Learning Scientist. In this role, you will leverage your expertise to drive innovation and development in cutting-edge research projects. Collaborate with a multidisciplinary team to push the boundaries of machine learning technology.

Your Role at Lila Sciences We are seeking a talented Senior Software Engineer to collaborate with our Machine Learning Engineers and Researchers. You will be instrumental in developing software that enhances Lila’s ML workflows and research tools. Join a dynamic team of engineers as you contribute to the development, support, and maintenance of Lila’s cutting-edge ML libraries and tools. Your Contributions Create and optimize high-performance, secure, and thoroughly documented Machine Learning libraries that implement algorithms crafted by our machine learning specialists. Develop CI/CD pipelines and integration tests to streamline ML workflows. Design repository architectures that adhere to consistent standards. Assist with debugging, logging, and ongoing maintenance of Ray-based compute environments. Establish data ingestion pipelines connecting lab data with the ML teams. Qualifications for Success A minimum of 8 years of software development experience in commercial environments using Go or Python. Proven track record in implementing scalable software solutions. Familiarity with MLOps systems and GitOps tools (ArgoCD, GitHub Actions). Experience with orchestration frameworks like Ray, Argo, or Airflow. Strong knowledge in containerization, Kubernetes, and infrastructure-as-code tools. Excellent listening skills and the ability to comprehend complex problems and algorithms. Outstanding problem-solving abilities and a collaborative mindset. Self-motivated and detail-oriented, eager to work with dynamic, skilled teams in a fast-paced, entrepreneurial environment. Preferred Qualifications Experience with monitoring and logging tools such as Prometheus and Grafana. Background in research engineering or scientific software development. About Lila Sciences Lila Sciences is at the forefront of scientific innovation, pioneering the world’s first scientific superintelligence platform and autonomous laboratory for life sciences, chemistry, and materials science. We are committed to transforming the landscape of discovery by applying AI to every facet of the scientific method. Our mission is to leverage scientific superintelligence to address humanity's most pressing challenges, empowering scientists to deliver solutions in health, climate, and sustainability with unprecedented speed and scale. Discover more about our vision at www.lila.ai.

Your Impact at Lila As a Senior or Principal Research Engineer specializing in Synthetic Data, you will play a pivotal role in shaping the vision, roadmap, and execution of our synthetic data initiatives. Your responsibilities will span from asset generation and simulation to integrating machine learning training and achieving measurable enhancements in model performance. Collaborating closely with our Research Engineering team, you will design, generate, and implement artificial datasets aimed at training, testing, and refining Lila’s platform to achieve our strategic objectives. What You Will Build Define and refine the synthetic data strategy along with a comprehensive multi-quarter roadmap. Create evaluation frameworks that effectively connect synthetic interventions with genuine model performance. Establish high standards for asset quality, diversity, thorough documentation, and reproducibility while fostering a robust review culture. What You Will Need to Succeed Over 6 years of experience in applied ML/ML systems, with at least 3 years leading industry initiatives, showcasing a strong track record in advanced algorithms and frameworks designed for large-scale synthetic data generation. More than 8 years of experience working with contemporary ML workflows, including Python, PyTorch, dataset tools, training loops, and evaluation frameworks; adept at profiling and optimizing GPU-intensive pipelines. Bonus Points For A proven history of constructing synthetic datasets from source data to significantly enhance model performance in specific domains. Experience with instruction fine-tuning and hill-climbing techniques. Ability to translate product requirements and feedback into a scalable synthetic data generation pipeline. Knowledge of quantization, distillation, routing, mixture-of-experts, and cost optimization at scale. Experience in compliance-heavy settings (HIPAA, PCI, FedRAMP) and with on-premises/VPC deployments. About Lila Lila Sciences stands at the forefront of innovation as the world’s first scientific superintelligence platform and autonomous lab, dedicated to life sciences, chemistry, and materials science. We are ushering in an era of limitless discovery by harnessing AI to enhance every facet of the scientific method. Our mission is to empower scientists to tackle humanity's most pressing challenges in health, climate, and sustainability at an unprecedented pace and scale. Discover more about our mission at www.lila.ai. If this sounds like an environment in which you would thrive, we encourage you to apply even if your experience doesn't perfectly align with every requirement listed.

Your Impact at Lila Join our team as a Machine Learning Scientist focused on pioneering multi-modal reasoning through vision-language models (VLMs) leveraging real-world scientific data, including figures, plots, and microscopy data from various sources. Your innovative designs will contribute to the advancement of Scientific Superintelligence. What You Will Be Building Lead cutting-edge research on multi-modal reasoning systems that analyze scientific data (images, plots, text, etc.) using advanced and custom VLMs. Design and implement training, adaptation, and test-time strategies (e.g., instruction tuning, supervised learning, RLHF, RAG) tailored for scientific comprehension tasks. Create datasets and benchmarks from authentic scientific artifacts (e.g., microscopy images, spectra, protocols) to evaluate model performance. Develop perception modules (e.g., OCR, table/structure recognition, plot parsing) for handling multi-modal data types. Collaborate with domain scientists and engineers to transition research into production-ready systems for enhancing scientific superintelligence. What You’ll Need to Succeed A graduate degree in a relevant discipline (Computer Science/AI, Applied Mathematics/Statistics, Electrical Engineering) or a physical sciences field (Materials, Chemistry, Physics) with a strong focus on machine learning; or equivalent research/industry experience. A proven track record in multi-modal machine learning or VLMs, evidenced by deployed systems, publications, or contributions to open-source projects. In-depth understanding of scientific QA/benchmarks and custom evaluation design. Experience with multi-modal fine-tuning, document parsing, dataset curation, and benchmarking. Robust engineering skills utilizing modern machine learning frameworks (e.g., PyTorch, Hugging Face). Strong communication and collaboration skills in cross-functional environments. Bonus Points For Experience with scientific data modalities in laboratory settings, such as microscopy images. Publications in leading ML/CV/NLP conferences or demonstrable impact in applied industrial research. Contributions to open-source multi-modal tools, evaluation suites, or datasets. About Lila Lila Sciences stands at the forefront of scientific superintelligence, operating as the world’s first platform and autonomous laboratory dedicated to life sciences, chemistry, and materials science. We are committed to revolutionizing discovery by harnessing AI to enhance every aspect of the scientific method.