Strong Compute jobs

Senior Principal Research Scientist, Computational Drug Discovery HitGen/LeadGen Team Lead North Chicago, IL, United States Company Description: About AbbVie AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com . Follow @abbvie on LinkedIn, Facebook , Instagram , X and YouTube. Job Description: Purpose This position brings an opportunity to make innovative contributions that will define how AbbVie leverages AI-enabled drug discovery across our small molecule portfolio. Reports to Head of Computational Drug Discovery (CDD) and will lead the computational HitGen/LeadGen (HGLG) team. Will implement and enable close collaboration between members of the HGLG team and partners in the Target Enabling Technologies (TET) and Global Medicinal Chemistry (GMEC) teams. Must possess a strong expertise in modern medicinal chemistry, including a deep understanding of modern computational and experimental strategies, and property-based drug design. The ideal candidate will have a strong and established background from having worked on a broad range of diverse early-stage campaigns, and an established external footprint and network. Past experience will have included mentorship of early/mid-career scientists in matrixed and/or direct reporting relationships. Responsibilities Consult with project team to establish desirable project-relevant hit/lead criteria, and assigning an HGLG member to the project team that

Applied AI/ML Scientist UAE Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. About The Role As an Applied AI Scientist in the FieldML team, you will be responsible for developing and customizing large language models and more broadly large-scale deep learning models to solve specific customer problems. You won't just advise; you will build. You will bridge the gap between state-of-the-art research and real-world applications by helping customers harness the power of the Cerebras Wafer-Scale Engine (WSE) for their AI initiatives. We are looking for experienced AI Scientists who are passionate about the "applied" side of machine learning - those

Sr. Member of Technical Staff Sunnyvale, CA Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. Cerebras Systems Inc. has multiple openings for Sr. Member of Technical Staff Title: Sr. Member of Technical Staff Job Duties: - Design and develop software features that support system resiliency and high availability, including automated recovery mechanisms and fault-tolerant architecture across distributed environments. - Develop and maintain cloud-based deployment workflows for AI inference software using AWS tools and services to support low-latency and scalable system performance. - Develop Python-based scripts and APIs to streamline data preprocessing, inference execution, and post-processing for real-time inference tasks. -

Thesis Quantum Computing and Generative Models (f/m/x) Location not specified SOME IT WORKS. SOME CHANGES WHAT'S POSSIBLE. SHARE YOUR PASSION. More than 90% of automotive innovations are based on electronics and software. That's why creative freedom and lateral thinking are so important in the pursuit of truly novel solutions. That's why our experts will treat you as part of the team from day one, encourage you to bring your own ideas to the table - and give you the opportunity to really show what you can do. Our team at the BMW Group explores innovative solutions in quantum computing and generative models to advance research in quantum chemistry. We offer you the opportunity to support pioneering projects in a collaborative environment. What awaits you? You will support the team in applying generative models to quantum chemistry challenges. Furthermore, you help to develop and implement quantum algorithms for research purposes. In addition, you participate in research and development activities to explore new applications of quantum computing. Please note that your thesis must be supervised by a university on your part. What should you bring along? Studies in computer science, engineering, physics or a related field. Strong programming skills, preferably in Python. Experience or coursework in machine learning. Interest in quantum computing and quantum chemistry. Ability to collaborate in a dynamic team environment. Good English skills. Would you like to support our team in advancing quantum computing and generative models? Then apply now! What do we o

Director, AI Storage Product Management City Remote Employee US | State/Province New Hampshire | Country USA Req ID: 133067 Region: Country USA State/Province: State/Province New Hampshire City Remote Employee US Summary Celestica's Hardware Product Solutions group has a critical opening for a Director, AI Storage Product Line Management position. This individual must possess a strong understanding of datacenter Artificial Intelligence (AI) computing to include AI server and AI storage requirements. This individual will be a product leader in this rapidly growing business, working closely with multiple functional teams within Celestica to drive the development of platforms that help Enterprises and Service Providers transform their businesses using AI technologies. The ideal candidate will have strong knowledge of hardware technologies such as AI servers & AI storage and have experience with hardware & software product management to include understanding the full product lifecycle (cradle to grave). The candidate will own critical product line management responsibilities and be an active contributor in setting up processes to increase the impact of strong product management practices. This opportunity requires excellent business, technical, problem-solving, and communication skills. The role is best suited for candidates in Bay Area. Detailed Description Drive AI storage & compute product strategy and establish optimal roadmap to include new products and services. Understand what will make AI storage & compute portfolio competitive and define winning features, pricing, launch/GA tar

Senior Performance Engineer, Inference Sunnyvale, CA Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. About The Role We are hiring a Senior Performance Engineer to join our Product team. You are an expert on state-of-the-art inference performance and will serve as our resident expert on how Cerebras stacks up against alternative inference providers on both price and performance. This role sits at the intersection of performance benchmarking from first principles and competitive intelligence. The role has two core pillars: - Performance Benchmarking You will build, run, and maintain reproducible benchmarks that measure Cerebras inference performance for real customer workloads. This

Account Executive (Cloud & AI Specialist) 2 Locations Meet the Team The ASEAN Cloud & AI business is a key growth area for Cisco with strong and consistent growth record. This role is ultimately responsible for the Go to Market strategy and growth for our Data Center products and solutions across ASEAN region. You will be required to work closely with the Worldwide solutions peers, internal account teams, CAI Architecture Sales teams and our partners. You will collaborate with the Sales team to shape/drive top priorities and core initiatives focused on long-range growth and profitability within country. Your Impact You play a critical role in enabling Cisco to take Data Center Virtualization Solutions to market in areas of Network & IT Infrastructure and Public/Private/Hybrid DC Cloud Solutions. Your role as a Regional Specialist requires a balance of strong grounded technical and sales/business experience as well as hands-on compute system skillset. You will be working closely with Cisco Cloud & AI (CAI) & Account Teams across all customer segments (Tier-1 Enterprises, Government Agencies, and Service Providers) to develop and drive growth of CAI business. The role will invariably include working on incubating, nurturing Transformational opportunities in customer journeys. You have strong experience in the following primary responsibilities that make-up the role: Engagement with technical decision makers and business infrastructure GMs within the Accounts with identified Data Center opportunities of AI, Networking, Compute, Storage, Automation, and Applications. Ability to drive technical solutions development for AI full stack systems solutioning, including AI Compute

AI Systems, Language & Reasoning Models Palo Alto, CA I US Remote About Unconventional Since 2022, AI has entered the mainstream, reshaping entire industries from education and software development to fundamental consumer behaviors. This revolution has created an unprecedented demand for computation - a demand that is now fundamentally limited by energy, not just in the datacenter, but at a global scale. At Unconventional, our mission is to solve this. We are rethinking computing from the ground up to build a new foundation for AI that is 1000x more efficient. We're doing this by exploiting the rich physics of semiconductors, mapping neural networks directly to the device physics rather than relying on layers of inefficient abstraction. The Role As a Member of Technical Staff, Language & Reasoning Models, you will drive the development of foundational language and reasoning models that fundamentally leverage the dynamics of our novel silicon. Your goal is to map the behaviors of modern language models directly onto the physics of our hardware. You will sit at the intersection of NLP/reasoning research and hardware codesign, proving that high-fidelity, large-scale language understanding and generation can be achieved natively on an unconventional computing substrate. What You'll Do - Model Development: Design, train, and scale next-generation language and reasoning architectures (such as transformers, state space models, diffusion/flow models, and deep equilibrium models) specifically tailored for unconventional compute. - Physics-Informed Architecture: Rethink standard sequence modeling to exploit the continuous-time dynamics of silicon, moving away from layers of inefficient digital abstraction. -

Kernel Engineer Bengaluru, Karnataka, India Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. About The Role As a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture. You will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize

Quantum Applications Scientist Harwell, England, UK Summary QuEra Computing UK is seeking a talented, impact-motivated theoretical researcher with strong expertise in quantum computing applications. You will be a part of the team aiming to co-design novel quantum simulation applications for QuEra's neutral-atom hardware. Working individually and as part of a team, you will interact with academic collaborators, clients, business partners, and other users of quantum computing to address fascinating challenges, from the inclusion of near-term error correction approaches in quantum simulation algorithms to the design of new application pipelines, for example in quantum materials simulation , quantum chemistry or nuclear physics. Qualifications - Ph.D. degree in physics, computer science, or a related discipline, or equivalent professional experience, - A strong background in quantum computing and/or quantum algorithms, including - expertise in quantum simulation applications, preferably in condensed matter physics, quantum materials, nuclear physics and/or quantum chemistry, - expertise in using and/or developing numerical simulation techniques of many-body systems and/or quantum circuits, for example using Pauli propagation, Clifford simulation, tensor networks (MPS, DMRG, etc.), exact diagonalisation, sparse matrix methods, density-functional theory, coupled-cluster + extensions, DMFT - experience in using quantum circuit programming and compilation, for example using Cirq, Qiskit, Tket, CUDA-Q - An exceptional publication record in relevant fields, - Ability to collaborate effectively in cross-functional teams Preferred Qualifications - Knowledge of quantum error correction schemes and quantum simulation in the fault-tolerant era, - Experience translating theoretical ideas and protocols to quantum computing hardware, and - Experience working with or knowledge

Software Development Manager , Serverless Compute Fabric New York, New York, USA AWS Serverless Compute is at the heart of the Serverless movement. It is a fast growing service that is becoming the default compute platform for a wide range of applications including executing untrusted and AI generated code in isolated environments with near-instant launch and resume capabilities. We are looking for a software development manager to lead feature development for Serverless Compute. This role requires ownership, autonomy, and an ability to deliver results. You should be a self-starter with a bias towards independent problem solving. Clear communication and prioritization will be important as you partner with Product Management to plan, and deliver experiences for customers of Serverless Compute Platform. You have a passion for managing complex technology projects and helping the team make strong business judgments. Experience building low-latency compute infrastructure is preferred. How do you know if you are a good fit for us? You are fascinated by the challenge of building innovative, global-scale software systems. You value the purposefulness and connect to customers in every action, decision and code delivered. You are inspired by difficult problems and by quickly finding solutions that will stand the test of time. You relish the opportunity to take active ownership for building and operating a service that delights customers. Why do we believe that we are a good fit for you? You'll be part of a team with smart leaders and engineers who value empathy, inclusion and thought diversity. We set

AI Silicon Physical Design Engineer Remote, California, United States; Sunnyvale, CA Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. About The Role Join our close-knit physical design team where you'll excel in synthesizing, placing, and routing high speed designs. Experience the full spectrum of physical design and implementation, collaborating closely with the RTL team and integrating these blocks seamlessly into the full-chip architecture. Skills & Qualifications - 10+ years of physical design & physical verification experience. - Strong knowledge of block level and full-chip physical verification methodology. - Strong experience in block/subsystem timing closure. - Expert at optimizing for the

Staff/Sr. ML Compute Efficiency Engineer Santa Clara, United States of America Scaling machine learning workloads across thousands of GPUs and TPUs creates challenges that few engineers ever encounter. In Apple's Machine Learning Platform Technologies organization, we build the infrastructure that powers large-scale ML training and inference workloads, bringing together expertise in distributed systems, machine learning infrastructure, and high-performance computing. As a performance engineer in the ML Compute Efficiency team, you'll tackle ambiguous systems challenges, identify inefficiencies and build solutions that maximize accelerator utilization, reduce idle and fragmented capacity, and minimize recovery periods. This includes analyzing accelerator performance, digging into various parallelism techniques, and refining workload scheduling and orchestration across the compute fleet. Characterize ML workload behavior through profiling, benchmarks and metrics. Dive into unfamiliar codebases to prototype changes, evaluate tradeoffs, and build production-ready solutions. Design systems for efficient recovery from failures and preemptions. Create tools to identify and alert bottlenecks across applications and frameworks. Use workload-driven insights to influence next-generation hardware selection and procurement decisions. Collaborate closely with ML researchers and infrastructure engineers to address inefficiencies. Drive impact through hands-on contribution and mentorship. Minimum Qualifications: Experience with large-scale distributed systems for AI/ML workloads running on GPUs or TPUs. Strong software engineering skills with experience developing and optimizing training frameworks (e.g. PyTorch, JAX) using C/C++ or Python. Experience working on cross-functional projects with ML research and infrastructure teams. Familiarity with model architectures and various training techniques. Bachelor's degree in Computer Science or equivalent experience, with 7+ years of industry experience. Preferred

Member of Technical Staff - Compute Infrastructure Palo Alto, CA; Seattle, WA ABOUT xAI xAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: We are building one of the world's largest AI supercomputers from the ground up. As part of the Compute Infrastructure team, you will own both the raw GPU supercomputer and the platform layer that runs on top of it. You will work across the full stack - from low-level GPU kernel optimizations and Linux kernel internals to massive-scale orchestration and virtualization - to make training and inference at xAI as fast, reliable, and scalable as possible. This is a broad, high-impact role that combines hardcore supercompute and compute infrastructure work. Your contributions will directly accelerate Grok's training speed and overall AI progress. RESPONSIBILITIES : - Design, build, and optimize massive GPU clusters for extreme-scale training and inference workloads - Develop and tune low-level CUDA

Senior Manager, Compute Accounting San Francisco, CA | Seattle, WA About Anthropic Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Senior Manager, Compute Accounting at Anthropic, you will own the end-to-end accounting for our compute expenses, ensuring accurate financial reporting and robust controls as we scale. You'll be responsible for the complete lifecycle of compute accounting-from contract review and compliance through accruals, prepaids, accounts payable reconciliation, expense classification, and commitment tracking. This role requires deep expertise in accounting for compute usage, strong data and analytical capabilities, and the ability to build scalable processes in a high-growth environment. You'll partner directly with the relevant Engineering, Legal, and Procurement teams to ensure our CSP contracts are properly reflected in our financial records and that we're capturing costs accurately and in compliance with our agreements. As Anthropic continues to grow rapidly, you'll play a critical role in establishing the financial controls and processes that enable us to manage significant compute spend with precision and confidence. Responsibilities: - - Own the complete accounting lifecycle for compute expenses, ensuring accurate and timely recording of all costs - Review and interpret CSP contracts to ensure proper accounting treatment and compliance with contractual terms - Design and implement accrual

Principal Engineer, Compute Fleet Management Bellevue, Washington # P-725 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems - from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. About the Team: Join the Core of Databricks Infrastructure The Compute Infra Team is the engine behind all of Databricks' products and Control Plane services. We build and scale the foundational compute infrastructure that enables every Databricks customer to succeed, operating one of the largest and most dynamic data and AI clouds in the world. Mission: Define the Future of Cloud Compute Efficiency and Scale As the Technical Lead for Compute Fleet Management, you won't just manage a fleet-you will set the standard for how Databricks consumes and optimizes compute across all three major clouds (AWS, Azure, and GCP). This is a mission-critical role with direct impact on our gross margin and customer experience. Your mandate includes: - Pioneering Fleet Optimization: Provisioning and pooling of O(Billion)s of cloud resources to achieve peak workload performance, industry-leading efficiency, and robust resource isolation. - Delivering Hyper-Scale Resilience: Build the architecture that guarantees horizontal scaling and resilience against zonal or even cloud account-level failures, ensuring Databricks is always on. - Owning the Critical Path: Lead the development of the lowest-dependency systems required to bootstrap and manage

Director / Senior Director, Critical Facility Operations Sunnyvale, CA Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. The Role At Cerebras, we build systems that redefine the scale of compute. That ambition extends beyond silicon into the infrastructure that powers it. We are looking for a Director / Sr. Director of Critical Facility Operations to lead the environments that enable next-generation AI workloads. This leader will own availability, operational integrity, and performance across a colocation-driven data center footprint-ensuring our infrastructure operates with precision, predictability, and zero room for error. This is not a traditional facilities role. You will operate at

AI Trainer - Computer Scientist (PST) Remote AI Trainer - Computer Scientist About Prolific Prolific is not just another player in the AI space - we are building the biggest pool of quality human data in the world. Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills. The role We're looking for people with Computer Science expertise to work as self-employed AI Trainers to help train and evaluate cutting-edge AI models from some of the world's biggest AI labs. If you have the necessary experience, we'll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a Domain Expert participant, where you'll get paid to train and evaluate powerful AI models. Researchers looking for your skills tend to pay up to £50/hr subject to the length of tasks available. If successful, you must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter. What you'll be doing in the role Completing AI training tasks such as analyzing, editing, and writing computer science-related content Judging the performance of AI on programming, algorithms, data structures, and systems prompts Improving cutting-edge AI models using your understanding of software engineering and computational thinking What you'll bring Background in Computer Science and ideally a degree in Computer Science or a closely related field Strong understanding of

Product Manager, Strategic Verticals San Francisco, California, United States Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. Our customers span leading AI Native companies, Fortune 500 Enterprises, Sovereign AI and Federal programs, and leading research institutions. Our mission is to deliver the platform that unlocks the next generation of AI applications, providing the fundamentally new capability to leverage the most intelligent models at real-time serving speeds. Why Cerebras? Here at Cerebras, we have built the world's first wafer-scale compute platform and software stack, purpose-designed to accelerate generative AI by over 10-20x what is possible on legacy processors today. AI developers

AI Trainer - Computer Scientist (CAN) Remote AI Trainer - Computer Scientist About Prolific Prolific is not just another player in the AI space - we are building the biggest pool of quality human data in the world. Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills. The role We're looking for people with Computer Science expertise to work as self-employed AI Trainers to help train and evaluate cutting-edge AI models from some of the world's biggest AI labs. If you have the necessary experience, we'll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a Domain Expert participant, where you'll get paid to train and evaluate powerful AI models. Researchers looking for your skills tend to pay up to £50/hr subject to the length of tasks available. If successful, you must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter. What you'll be doing in the role Completing AI training tasks such as analyzing, editing, and writing computer science-related content Judging the performance of AI on programming, algorithms, data structures, and systems prompts Improving cutting-edge AI models using your understanding of software engineering and computational thinking What you'll bring Background in Computer Science and ideally a degree in Computer Science or a closely related field Strong understanding of

Staff Kernel Optimzation Engineer Remote, California, United States Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. About The Role As a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture. You will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed

AI Trainer - Computer Scientist (EST) Remote AI Trainer - Computer Scientist About Prolific Prolific is not just another player in the AI space - we are building the biggest pool of quality human data in the world. Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills. The role We're looking for people with Computer Science expertise to work as self-employed AI Trainers to help train and evaluate cutting-edge AI models from some of the world's biggest AI labs. If you have the necessary experience, we'll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a Domain Expert participant, where you'll get paid to train and evaluate powerful AI models. Researchers looking for your skills tend to pay up to £50/hr subject to the length of tasks available. If successful, you must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter. What you'll be doing in the role Completing AI training tasks such as analyzing, editing, and writing computer science-related content Judging the performance of AI on programming, algorithms, data structures, and systems prompts Improving cutting-edge AI models using your understanding of software engineering and computational thinking What you'll bring Background in Computer Science and ideally a degree in Computer Science or a closely related field Strong understanding of

Site Reliability Engineer - Ops & Automation Sunnyvale CA or Toronto Canada Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. About the Role We are building a high-performance SRE function to support one of the world's fastest-growing AI inference services, powered by the Wafer-Scale Engine (WSE), helping deliver infrastructure for frontier-class models from leading model builders such as OpenAI. This role offers immediate ownership of real production systems at a growing scale, direct mentorship from seasoned engineers, and close collaboration with incoming Staff SREs who will focus on long-term automation. After ~1 month of shared hands-on operations with the Staff

AI Trainer - Computer Scientist (UK) Remote AI Trainer - Computer Scientist About Prolific Prolific is not just another player in the AI space - we are building the biggest pool of quality human data in the world. Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills. The role We're looking for people with Computer Science expertise to work as self-employed AI Trainers to help train and evaluate cutting-edge AI models from some of the world's biggest AI labs. If you have the necessary experience, we'll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a Domain Expert participant, where you'll get paid to train and evaluate powerful AI models. Researchers looking for your skills tend to pay up to £50/hr subject to the length of tasks available. If successful, you must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter. What you'll be doing in the role Completing AI training tasks such as analyzing, editing, and writing computer science-related content Judging the performance of AI on programming, algorithms, data structures, and systems prompts Improving cutting-edge AI models using your understanding of software engineering and computational thinking What you'll bring Background in Computer Science and ideally a degree in Computer Science or a closely related field Strong understanding of