Machine Learning Scientist / Senior Machine Learning Scientist at altoslabs | Cambridge, UK

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.

Innovate and Create Models from Scratch! At Flagship Pioneering, we are dedicated to launching pioneering companies that challenge the status quo. Within our Flagship Labs, small, agile teams develop new technical theses, rigorously test them, and build ventures around groundbreaking concepts. We are assembling an exceptional machine learning team within our newly established venture, Flagship Labs 120. Our focus is on uncovering hidden structures from complex measurement data of intricate physical systems, often necessitating mechanism-informed modeling, carefully designed inductive biases, and principled methodologies for inverse problems. This is a pioneering role dedicated to innovative modeling, moving beyond standard optimization tasks. You will have the opportunity to design, prototype, test, and refine novel approaches that establish the technical foundation of our platform starting from day one.

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.

Our MissionAt Altos Labs, our mission is to rejuvenate cell health and resilience, aiming to reverse diseases, injuries, and the associated disabilities that arise throughout life.For further details, visit our website at altoslabs.com.Our ValuesWe embrace a singular value at Altos: Everyone Owns Achieving Our Inspiring Mission.Diversity at AltosWe hold a firm belief that diverse perspectives are crucial to scientific advancement and inquiry. At Altos, outstanding scientists and industry leaders collaborate from across the globe to further our shared mission. We prioritize creating a sense of belonging, ensuring that every employee feels valued for their unique contributions. We are collectively responsible for maintaining a diverse and inclusive workplace.Your Contributions to AltosIn the role of Senior or Principal Machine Learning Scientist, you will be instrumental in the development of generative AI/ML models for multi-modal, multiscale biology, spanning from virtual cells to agentic target assessment. We seek a hands-on, innovative, and collaborative individual to join our multidisciplinary team of scientists and engineers dedicated to transforming the treatment of aging and disease. The ideal candidate will flourish in a dynamic environment that values teamwork, transparency, scientific excellence, originality, rigor, and integrity.

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.

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.

Your Impact at Lila As a Machine Learning Scientist specializing in Scientific Reasoning, you will be at the forefront of advancing AI systems designed to think like scientists. Your role involves crafting innovative frameworks that extend the capabilities of LLM-based reasoning methods while also developing scalable systems that enhance Lila’s platforms. This position merges profound theoretical insights with hands-on ML engineering, facilitating breakthroughs in the generation, testing, deployment, and optimization of scientific hypotheses. What You Will Be Creating Develop and formalize frameworks for scientific reasoning using LLMs, incorporating structured prompting, reasoning chains, and computational strategies at test time. Investigate and implement techniques for in-context learning, self-reflection, and adaptive reasoning within scientific discovery processes. Create scalable model prototypes aimed at addressing cutting-edge scientific challenges. Collaborate with scientists and engineers to embed domain knowledge into reasoning systems that unify symbolic and statistical methodologies.

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 Contribution at Lila Sciences As a Robotics Scientist at Lila Sciences, you will spearhead the research and innovation of autonomous robotic systems that form the intelligent physical backbone of our cutting-edge scientific superintelligence platform. You will be instrumental in developing groundbreaking algorithms and deploying advanced robotic solutions that engage seamlessly with human scientists and intricate laboratory settings. Your efforts will propel our mission forward by establishing fully autonomous workflows for scientific exploration, merging state-of-the-art robotics, machine learning, and systems engineering. Projects You Will Undertake Innovating advanced methodologies for precise and dexterous robotic manipulation that utilize foundation models, reinforcement learning, diffusion-based techniques, and human input, enabling adaptable and intelligent robotic systems capable of executing complex tasks in a variety of scientific environments. Creating novel frameworks for human-robot interaction that integrate imitation learning and learning from human feedback, demonstrations, and corrections, fostering intelligent robotic agents that can smoothly blend into human scientific workflows and swiftly adapt to new experimental scenarios. Enhancing dexterous manipulation research through avant-garde machine learning techniques, including diffusion models and adaptive learning algorithms, synthesizing multi-modal sensing (tactile, visual, and linguistic) to develop generative skill representations and sophisticated motor learning policies for intelligent robotic systems. Designing autonomous robotic systems equipped with trust calibration mechanisms, allowing intelligent agents to dynamically modify their behaviors based on contextual information in challenging scientific tasks.

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.

Collaboration Fuels Innovation. Join Roku - Revolutionizing TV ViewingAs the leading TV streaming platform in the U.S., Canada, and Mexico, Roku is on a mission to empower every television worldwide. Pioneering the streaming experience, we connect viewers to their favorite content, support publishers in audience growth and monetization, and provide advertisers with exceptional tools for consumer engagement.From day one at Roku, your contributions will be valued. We are a rapidly expanding public company where every team member plays an essential role. This is your chance to impact millions of TV streamers globally while gaining significant experience across diverse disciplines. About Our TeamThe Advertising Performance team is dedicated to optimizing the performance of all participants in the advertising ecosystem, including advertisers, publishers, and Roku itself. Our systems and solutions leverage various disciplines and technologies for real-time, multi-objective optimization on a large scale with minimal latency. Utilizing Machine Learning, Reinforcement Learning, AI, and Optimization Systems, we tackle a wide array of complex challenges. Central to our efforts is our Machine Learning, Experimentation, and Inference Platform that supports the entire operational landscape.

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.

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.

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.

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!

Your Contribution at Lila At Lila, we are assembling a dynamic and empowered AI safety team dedicated to proactively addressing the potential risks associated with scientific superintelligence. This team will collaborate closely with all core departments, including science, model training, and lab integration, to craft a customized safety strategy that aligns with our unique objectives and deployment methods. Key responsibilities will encompass the development of technical safety strategies, engagement with the broader ecosystem, and the creation of essential technical documentation, including risk assessments and capability evaluations. Your Key Responsibilities Design and execute evaluations to identify scientific risks—focusing on both established and emerging threats—from state-of-the-art scientific models integrated with automated physical laboratories. Develop initial proof-of-concept safety measures, such as machine learning models designed to detect and mitigate unsafe behaviors from scientific AI models and physical laboratory outputs. Gain a comprehensive understanding of various model capabilities, primarily within scientific contexts but also extending to non-scientific domains (e.g., persuasion, deception) to shape Lila's overarching safety strategy. Engage in high-quality research initiatives as needed to evaluate and restrict scientific capabilities effectively. Qualifications for Success A Bachelor's degree in a relevant technical field (e.g., computer science, engineering, machine learning, mathematics, physics, statistics) or equivalent experience. Proficient programming skills in Python and hands-on experience with machine learning frameworks (such as Inspect) for large-scale evaluations and structured testing. Demonstrated experience in constructing evaluations or conducting red-teaming exercises pertaining to CBRN/cyber risks or frontier model capabilities, encompassing both unsafe and benign attributes. Background in designing and/or implementing AI safety frameworks in cutting-edge AI enterprises. Exceptional ability to communicate intricate technical concepts and issues to audiences without technical expertise. Desirable Qualifications A Master’s or PhD in a field pertinent to safety evaluations of AI models within scientific areas or another technical discipline. Publications in AI safety, evaluations, or model behavior at leading ML/AI conferences (such as NeurIPS, ICML, ICLR, ACL) or model release documentation. Experience exploring risks arising from novel scientific advancements (e.g., biosecurity, computational biology) or utilizing specialized scientific tools (e.g., large-scale foundational models in science).

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.

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!