Cerebras Systems builds the worlds 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 global corporations across multiple industries, national labs, and top-tier healthcare systems. In January, we announced a multi-year, multi-million-dollar partnership with Mayo Clinic, underscoring our commitment to transforming AI applications across various fields. In August, we launched Cerebras Inference, the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. About The Role Cerebras Systems is a pioneer in large-scale AI Supercomputers. These multi-exaflop supercomputers are deployed in some of the biggest datacenters. These supercomputers are built using our Wafer-Scale Cluster technology - a cluster of several Wafer Scale Engine (WSE) chips. The Cluster engineering team is responsible for delivering software that are all-things related to cluster. Responsibilities Automate bare-metal configuration of networking, OS, and application software in large clusters of Cerebras WSE, servers, and switches.Additional push button workflows for cluster upgrades, downgrades, and security patching with key metrics to minimize downtime on clusters.An orchestration and scheduler system for resource allocation, job submission placements for a multi-user environment on a cluster.Seamless support for both on-premise and cloud mode deployment and operations.A robust system for monitoring, detecting and handling failures for a variety of resources on the clusters (including High Availability of clusters).Broad cluster and job monitoring and visualization capabilities, along with alerting systems.User facing tools to monitor the status of jobs and collect metrics.Administrator facing tools to manage and operate large clusters. Skills And Qualifications Strong track record of software architecture, system design and development for over 6 years or more.Strong track record of development in distributed cluster environment.Strong understanding of Kubernetes (K8s) software ecosystem, Prometheus and Grafana.Strong development skills in GoLang, Python, bash.Strong debugging skills with distributed systems.Strong skill to develop tests for the new features and regress old features. Location Bangalore, India. Why Join Cerebras People who are serious about software make their own hardware. At Cerebras we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:Build a breakthrough AI platform beyond the constraints of the GPU.Publish and open source their cutting-edge AI research.Work on one of the fastest AI supercomputers in the world.Enjoy job stability with startup vitality.Our simple, non-corporate work culture that respects individual beliefs.Read our blog: Five Reasons to Join Cerebras in 2025. Apply today and become part of the forefront of groundbreaking advancements in AI! Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Cerebras Systems builds the worlds 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 global corporations across multiple industries, national labs, and top-tier healthcare systems. In January, we announced a multi-year, multi-million-dollar partnership with Mayo Clinic, underscoring our commitment to transforming AI applications across various fields. In August, we launched Cerebras Inference, the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. Responsibilities Work with RTL designers and software engineers to ensure a high-quality design that works first silicon. Develop detailed test and coverage plans based on the micro-architecture. Create verification methodologies and reusable environments, including components such as stimulus, checkers, assertions, and coverage. Write tests, manage regressions, gather coverage, and debug test failures. Skills and Qualifications Great debugging and problem-solving skills. Deep knowledge of SystemVerilog testbench language, DPI and UVM. Excellent programming skills and knowledge of software engineering practices including object-oriented design. Experience developing scalable and portable testbenches and components. Experience with verification methodologies and tools such as simulators, waveform viewers, build and run automation, coverage collection, gate level simulations. Proficient in a scripting language such as Python or Perl. Good interpersonal skills and ability desire to work as a standout colleague are a must. Extremely self-motivated and eager to solve problems 5 years of Design Verification experience. Desired Skills and Qualifications Knowledge of pipelined processor architecture. Experience in writing reference models in C++. BS or MS in Computer Science or Electrical Engineering. Why Join Cerebras People who are serious about software make their own hardware. At Cerebras we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras: Build a breakthrough AI platform beyond the constraints of the GPU. Publish and open source their cutting-edge AI research. Work on one of the fastest AI supercomputers in the world. Enjoy job stability with startup vitality. Our simple, non-corporate work culture that respects individual beliefs. Read our blog: Five Reasons to Join Cerebras in 2025. Apply today and become part of the forefront of groundbreaking advancements in AI! Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Cerebras Systems builds the worlds 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 global corporations across multiple industries, national labs, and top-tier healthcare systems. In January, we announced a multi-year, multi-million-dollar partnership with Mayo Clinic, underscoring our commitment to transforming AI applications across various fields. In August, we launched Cerebras Inference, the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. About The Role As Senior ML Quality Engineer, you ensure quality of Cerebras SW across all supported ML workloads and workflows. You will be part of MIQ (ML Integration and Quality) team that will focus on SW components feature testing, ML training accuracy and performance, pre deployment/production validation, validating customer workloads and workflows. As part of this role, you will influence the best testing practice, good debugging methodology, effective cross team communication and advocate for world-class products. Responsibilities Drive quality of various software and hardware components of Cerebras solution to ensure accuracy, performance and usability of model trainings. Bring good testing methodology, effective communication and strong debugging skills to the team. Demand the highest quality from all components within the Cerebras environment. Ability to automate workflows, setup testbeds and build tools to effectively monitor and debug issues. Implement creative ways to break Cerebras software and identify potential problems. Break down complex tasks into smaller tasks. Be a problem solver. Be a thought leader. Ability to work in a fast-paced environment and make the necessary prioritizations and judgements which affects productivity at a company level. Skills And Qualifications 5+ years of relevant industry experience in Software quality and testing areas. Experience testing AI/ML models and evaluation of the model quality. Stong automation and programming skills using one or more programming languages like Python, C++ or go. Experience in testing compute/machine learning/networking/storage systems within a large-scale enterprise environment. Experience in debugging issues across scale out deployment. Experience in putting together thorough test-plans. Experience working effectively across teams, including product development, product management, customer operations, and field teams. Preferred Skills And Qualifications Knowledge of ML workflows and frameworks. Knowledge of basic storage and networking protocols. Hands-on experience with training LLMs. Hands-on experience working with containers, Kubernetes. Why Join Cerebras People who are serious about software make their own hardware. At Cerebras we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:Build a breakthrough AI platform beyond the constraints of the GPU.Publish and open source their cutting-edge AI research.Work on one of the fastest AI supercomputers in the world.Enjoy job stability with startup vitality.Our simple, non-corporate work culture that respects individual beliefs.Read our blog: Five Reasons to Join Cerebras in 2025. Apply today and become part of the forefront of groundbreaking advancements in AI! Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Cerebras Systems builds the worlds 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 global corporations across multiple industries, national labs, and top-tier healthcare systems. In January, we announced a multi-year, multi-million-dollar partnership with Mayo Clinic, underscoring our commitment to transforming AI applications across various fields. In August, we launched Cerebras Inference, the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. About the Role A highly motivated engineer skilled in data processing to help build insights from the data collected from our WSE and Data Center. The role is focused on turning complex data streams into actionable insights to help improve system performance, reliability and overall efficiency. Responsibilities Design and implement a robust framework for visualizing and analyzing complex datasets. Generate insights from data and translate them into actionable recommendations. Collaborate with cross-functional teams to understand their data needs and provide solutions. Ensure data quality, integrity, and consistency throughout the analysis process. Query time series data via SQL and post process using Python. Work with the data and systems teams to define requirements and tools. Skills and Qualifications B.S. degree with 5+ years of software development experience. At least 3+ years of collaborative development in Python/SQL or similar languages. Working with Git, Continuous Integration (Jenkins) and Agile development processes. Writing high quality testable code and following good software practices. Preferred Skills and Qualifications Experience with cloud-based data platforms (e.g., AWS, Azure, GCP). Knowledge of data warehouse concepts and ETL processes. Self-starter capable of owning and driving requests to closer. Basic understanding of Matlab code to convert to Python. Data visualization/Processing and ability to define schemas based on user needs. Familiar with Grafana, Prometheus, time-series databases, designing web apps. Why Join Cerebras People who are serious about software make their own hardware. At Cerebras we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:Build a breakthrough AI platform beyond the constraints of the GPU.Publish and open source their cutting-edge AI research.Work on one of the fastest AI supercomputers in the world.Enjoy job stability with startup vitality.Our simple, non-corporate work culture that respects individual beliefs.Read our blog: Five Reasons to Join Cerebras in 2025. Apply today and become part of the forefront of groundbreaking advancements in AI! Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Cerebras Systems builds the worlds 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 global corporations across multiple industries, national labs, and top-tier healthcare systems. In January, we announced a multi-year, multi-million-dollar partnership with Mayo Clinic, underscoring our commitment to transforming AI applications across various fields. In August, we launched Cerebras Inference, the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. About The Role As a Kernel Engineer on our team, you will work with leaders from industry and academia at the intersection of hardware and software to develop state-of-the-art solutions for emerging problems in AI and HPC. Our team of developers is responsible for the design, implementation, validation, and performance tuning of deep learning operations on highly parallel custom processors. We are developing a library of parallel and distributed algorithms to maximize hardware utilization and accelerate the training of deep neural networks to unprecedented speeds. Responsibilities Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms. Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system. Using mathematical models and analysis to measure the software performance and inform design decisions. Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries. Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks. Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems Skills And Qualifications Bachelor s, Master s, PhD or foreign equivalents in Computer Science, Computer Engineering, Mathematics, or related fields. Understanding of hardware architecture concepts must be comfortable learning the details of a new hardware architecture. Skilled in C++ and Python programming languages. Good knowledge of library and/or API development best practices. Strong debugging skills and knowledge of debugging complex software stack. Preferred Skills And Qualifications Experience in kernel development and/or testing. Familiarity with parallel algorithms and distributed memory systems. Experience in programming accelerators such as GPUs and FPGAs. Familiarity with Machine Learning neural networks and frameworks such as TensorFlow and PyTorch. Familiarity with HPC kernels and their optimization. Why Join Cerebras People who are serious about software make their own hardware. At Cerebras we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:Build a breakthrough AI platform beyond the constraints of the GPU.Publish and open source their cutting-edge AI research.Work on one of the fastest AI supercomputers in the world.Enjoy job stability with startup vitality.Our simple, non-corporate work culture that respects individual beliefs.Read our blog: Five Reasons to Join Cerebras in 2025. Apply today and become part of the forefront of groundbreaking advancements in AI! Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.