Strong Compute jobs

Quantum Research Scientist, Processor Test & Measurement, AWS Center for Quantum Computing Pasadena, California, USA The Amazon Web Services (AWS) Center for Quantum Computing in Pasadena, CA, is looking to hire a Quantum Research Scientist in the Processor Test and Measurement group. You will join a multi-disciplinary team of theoretical and experimental physicists, materials scientists, and hardware and software engineers working at the forefront of quantum computing. You should have a deep and broad knowledge of experimental measurement techniques. Candidates with a track record of original scientific contributions will be preferred. We are looking for candidates with strong engineering principles, resourcefulness and a bias for action, superior problem solving, and excellent communication skills. Working effectively within a team environment is essential. As a research scientist you will be expected to work on new ideas and stay abreast of the field of experimental quantum computation. Key job responsibilities We are looking to hire a Research Scientist to develop and test novel calibration and optimization tools for Quantum Error Correction on large scale quantum processors. You will be on a team of engineers and scientists at the frontier of quantum processor control and error correction. You are expected to take part in high-impact research projects that intersect with our engineering roadmap. We are looking for candidates with strong engineering principles and resourcefulness. Organization and communication skills are essential. A day in the life About the team Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform.

Advanced Technology: AI/ML Research Scientist Sunnyvale, CA; Toronto, Ontario, Canada; Vancouver, British Columbia, 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 Team Cerebras builds wafer-scale AI processors-single chips delivering tens of PB/s of memory bandwidth and a dataflow architecture that accelerates at a granularity no multi-device system can match. The Advanced Technology Group (ATG) is Cerebras ' pathfinding organization. We work ahead of product to explore new architectures, demonstrate breakthrough performance on scientific and AI workloads, and shape the technical roadmap for future Cerebras hardware and software. Our work regularly appears at top-tier venues (Supercomputing, SIAM, IEEE,

Sr. Quantum Research Scientist, AWS Center for Quantum Computing Pasadena, California, USA The Amazon Web Services (AWS) Center for Quantum Computing in Pasadena, CA, is looking to hire a Quantum Research Scientist in the Processor Test and Measurement group. You will join a multi-disciplinary team of theoretical and experimental physicists, materials scientists, and hardware and software engineers working at the forefront of quantum computing. You should have a deep and broad knowledge of experimental measurement techniques. Candidates with a track record of original scientific contributions will be preferred. We are looking for candidates with strong engineering principles, resourcefulness and a bias for action, superior problem solving, and excellent communication skills. Working effectively within a team environment is essential. As a research scientist you will be expected to work on new ideas and stay abreast of the field of experimental quantum computation. Key job responsibilities We are looking to hire a Senior Research Scientist to develop and test novel calibration and optimization tools for Quantum Error Correction on large scale quantum processors. You will be a technical leader on a team of engineers and scientists at the frontier of quantum processor control and error correction. You are expected to develop & lead high-impact research projects that intersect with our engineering roadmap. We are looking for candidates with strong engineering principles and resourcefulness. Organization and communication skills are essential. A day in the life About the team Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud

Engineering Manager, Inference ML Runtime 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 The Inference ML Engineering team at Cerebras builds the runtime, APIs, and systems that power the fastest generative AI inference platform in the world. As an Engineering Manager, Inference ML Runtime , you will lead a team responsible for designing and scaling the systems that enable seamless execution of state-of-the-art AI models on Cerebras hardware. You will operate at the intersection of machine learning, distributed systems, and high-performance runtime engineering , translating cutting-edge research into production-ready infrastructure to serve

Global Account Manager, NACI OCI AI & Healthcare United States, US 5-15 years of experience in strategic enterprise technology sales within high-tech industries Strong background selling into Health & Science organizations including enterprise pharma, biotech, med tech, healthcare, or life sciences companies Demonstrated success managing complex enterprise sales cycles and large strategic accounts Strong technical acumen with the ability to understand sophisticated infrastructure requirements, customer challenges, and solution architectures Experience collaborating across cross-functional teams including engineering, product, legal, finance, and executive leadership Expertise negotiating enterprise agreements and building complex commercial contracts Strong communication, presentation, and executive relationship management skills Proven ability to manage multiple high-value opportunities simultaneously in a fast-paced environment Preferred Qualifications Experience selling high performance computing (HPC), AI infrastructure, cloud infrastructure, GPU compute, or related technologies Familiarity with technical computing environments supporting life sciences and scientific research workloads Experience supporting organizations running computational chemistry, molecular modeling, genomics, drug discovery, simulation, or AI-driven research platforms Knowledge of industry regulatory frameworks, data governance, and compliance standards relevant to healthcare and life sciences Ideal Candidate Profile The ideal candidate is a highly strategic and entrepreneurial sales leader who combines executive-level customer engagement skills with a strong desire to operate hands-on in complex, high-impact enterprise pursuits. This role is well suited for individuals who have experience leading teams, owning large strategic accounts, or managing global business responsibilities and are energized by the opportunity to directly shape and scale a rapidly growing AI infrastructure business. Successful candidates will bring a builder mentality and

Principal Engineer, Inference Cloud 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. Location: Sunnyvale We're hiring a Principal Engineer for our Inference Cloud Platform. This team owns the cloud layer behind our Inference Service, including availability, latency, reliability, and multi-region scale. This is one of the most senior IC roles on the team, for someone who can identify the highest-leverage platform problems, set direction across multiple teams, define long-term architecture, and write production code on critical paths. Many of the key decisions are ambiguous at the outset; you'll need to frame the problem, make tradeoffs, and drive execution

Full Stack Engineer – Manufacturing Test 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 As a Full Stack Engineer focusing on Cerebras' manufacturing test platform, you will design, build, and maintain a comprehensive test software solution for all stages of manufacturing - from individual components to complete Cerebras systems. You will collaborate cross-functionally with hardware design, engineering, operations, and data analytics teams to develop user interfaces and data processing frameworks that directly impact manufacturing efficiency, quality, and scalability. Responsibilities - Collaborate with hardware engineers and test developers to create frameworks that facilitate the development, validation,

Playtest Lead — ClusterCraft Contract / part-time · ~8-10 hrs/week · Sydney, NSW ClusterCraft is a tycoon/resource manager style game about running an AI compute cluster - power, cooling, GPUs, networking, training workloads, and the costs that tie them together. Built as a game/simulator for our real product. After a year of dev, we're ready for players. See what it looks like: https://www.youtube.com/playlist?list=PLteq7Tjf0g7To2nG5PPfvCX9KYmc0pctc The job Run 5 playtest sessions/week. Source testers, schedule, run, synthesize, hand structured feedback to devs. Sessions are 10-30 min today; we want them longer. The hard part ClusterCraft needs feedback from two audiences: tycoon gamers and infra/FinOps people. If you already have a foothold in either community, that's most of why we'd hire you. Bonus, not required Tune variables and level design yourself if you're technical. Logistics Initial onboarding sessions for a few hours with our team for you to understand the simulator and its features. Work hours of your choosing (subject to playtester availability) most of the time.. (Most of our team centers around Sydney time zone.) Rate depends on experience and network - tell us what you'd want. About us Strong Compute makes software manage high performance compute assets across multiple cloud vendors. We are a startup, largely based in Sydney and have been in operation for over 4 years.

Electronic Imaging Technician II, Computed Tomography Folsom, California, United States of America Embrace the role of an Electronic Imaging Technician II and play a vital role in supporting advanced diagnostic imaging systems. You'll maintain, troubleshoot, and ensure data quality across multiple imaging modalities. If you have strong technical skills, attention to detail, and a passion for healthcare technology, this is your opportunity to make an impact.

Applied Machine Learning Research Scientist 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 As an Applied Machine Learning Research Scientist at Cerebras, you will play a key role in turning modern machine learning techniques into scalable, high-performance systems. This role sits at the intersection of modeling and systems focused not on publishing new algorithms, but on understanding how they work and making them run effectively at scale. Your work will directly impact how large language models (LLMs) are trained, optimized, and deployed on one of the most advanced AI platforms in the

Manager, Business 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. About The Role This role is a high-leverage seat in that build and a deliberate apprenticeship into operating leadership. You will create the business operations, analytics, and execution system that keeps decision-ready insight flowing as the company scales. You will be embedded with operators, turning messy operational reality into durable processes, clear metrics, and repeatable operating rhythms. You will report to the Head of FP&A and work in close partnership with the COO and operations leadership. Why now Cerebras is scaling to meet accelerating demand for fast

Senior Cloud Architect (AWS) New Haven, CT At Quantum Circuits Inc., we are building the world's first truly algorithmic quantum computers to achieve transformational computing capabilities. Our full-stack quantum computing platform uses dual-rail superconducting devices along with a modular, robust, and scalable architecture. Our unique approach is based on a decade of technology research and breakthroughs at Yale University's world-renowned quantum labs. We are seeking a highly skilled and self-motivated Senior Cloud Architect to join our dynamic team. The ideal candidate has a strong background in leading the design, implementation, and continuous improvement of our cloud infrastructure. This is a senior, hands-on role ideal for a systems thinker who can architect complex distributed systems, guide modernization efforts, and contribute directly to high-priority cloud initiatives. Our cloud-based applications frequently interface with specialized hardware platforms, including embedded systems and scientific instrumentation, and support a range of data-intensive workloads. While direct experience with these systems isn't required, a strong conceptual understanding of Linux internals, embedded environments, or FPGA-based architectures will enable you to architect more effective, integrated solutions. You'll be expected to work independently, lead projects from concept through delivery, and collaborate cross-functionally to align technical solutions with organizational objectives. At Quantum Circuits Inc., we are building the world's first truly algorithmic quantum computers to achieve transformational computing capabilities. Our full-stack quantum computing platform uses dual-rail superconducting devices along with a modular, robust, and scalable architecture. Our unique approach is based on a decade of technology research and breakthroughs at Yale University's world-renowned

Performance Engineer Toronto, Ontario, 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 Join Cerebras as a Performance Engineer within our innovative Runtime Team. Our groundbreaking CS-3 system, hosted by a distributed set of modern and powerful x86 machines, has set new benchmarks in high-performance ML training and inference solutions. It leverages a dinner-plate sized chip with 44GB of on-chip memory to surpass traditional hardware capabilities. This role will challenge and expand your expertise in optimizing AI applications and managing computational workloads primarily on the x86 architecture that run our Runtime driver. Responsibilities - Focus on CPU

Quantum Scientist - Time-to-Solution & Benchmarking Albuquerque, NM, USA Summary QuEra Computing is seeking a Quantum Scientist to develop system- and algorithm-level performance models for large-scale neutral-atom quantum computers. This role focuses on translating device- and architecture-level models into quantitative estimates of algorithmic fidelity, runtime, and time-to-solution for representative quantum workloads. Working at the interface of quantum algorithms, architecture and benchmarking, you will analyze how hardware constraints and effective error models impact end-to-end computational performance. You will develop system-level performance and runtime models that map device and architecture characteristics to algorithmic success probability, throughput, and time-to-solution. You will collaborate closely with hardware theory, experimental, and application development teams. Your work will directly support internal design decisions and external benchmarking efforts, including participation in programs such as DARPA's Quantum Benchmarking Initiative (QBI). The ideal candidate combines deep theoretical understanding with practical data-driven insight. Qualifications - 5+ years of experience in performance modeling, simulation, or analysis of quantum systems or other complex computational/physical systems. - Strong background in quantum information science, computational physics, or a closely related quantitative discipline. - Proficiency in numerical modeling and data analysis using Python or Julia. - Demonstrated ability to analyze experimental or simulated data and correlate results with abstracted models. - Strong written and verbal communication skills for technical documentation and cross-disciplinary collaboration. Preferred Qualifications - Experience with benchmarking or performance modeling in quantum computing platforms (neutral atoms, ions, superconducting qubits, or similar). - Experience developing or using abstracted error and performance models to evaluate system-

Full Stack Software Engineer - ML Compute Capacity Santa Clara, United States of America Scaling machine learning workloads across thousands of accelerators 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 senior engineer on the ML Compute Capacity team, you will design, build, and operate the production systems that ensure compute resources are optimally distributed throughout the company. You'll work across the stack - from data pipelines and backend services to APIs and interactive frontends - developing telemetry systems, optimization algorithms, policies, and intuitive tools for managing demand and improving efficiency across Apple's largest accelerator fleet. Our small, nimble team works in a high-autonomy, fast-paced environment, and we're passionate about digging into data patterns, laying out the performance characteristics of an entire distributed system, and knowledge sharing. If the opportunity to own and operate services that scale, stay highly available, and "just work" excites you, then please reach out to us! Build and operate demand and capacity planning systems Build data pipelines and telemetry systems that ingest, normalize, and serve fleet-wide utilization and cost data across multi-tenant and heterogeneous fleets Develop observability infrastructure - monitoring, alerting, and dashboards - that surfaces real-time fleet health and efficiency signals Drive innovation in forecasting, optimization, and supply chain management tooling that works at scale Build end-to-end tooling - from data models and

Solutions Architect, Solutions Architecture Taipei City, TWN Do you like helping hi-tech and semiconductor companies solve their most complex technical challenges? Would you like to do this using the latest cloud computing technologies including GenAI and agentic AI? Do you have a passion for enabling chip designers and product engineers to innovate faster and more efficiently through cloud modernization? AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing accounts to enterprise-level customers. This is an on-site position requiring regular presence at AWS offices and customer locations to deliver hands-on technical engagement and build strong customer relationships. As a Solutions Architect on the Hi-Tech & Semiconductor team, you will have the opportunity to help shape and deliver on a strategy to build mind share and broad use of AWS services - including compute, storage, networking, analytics, AI/ML, Generative AI, and HPC - within hi-tech and semiconductor accounts pursuing cloud modernization and digital transformation. You will be the bridge between our customers' most complex computational challenges and AWS's most advanced cloud infrastructure capabilities. You will own the technical engagement and ultimate success around specific implementation projects, with a strong focus on: Cloud Modernization & Infrastructure Optimization: Helping customers modernize their infrastructure, optimize compute-intensive and memory-intensive workloads, and transition to cloud-native architectures Compute-Intensive Workload Architecture: Architecting scalable solutions for demanding engineering workloads - including frontend design (RTL, synthesis, simulation), backend design (place and route, timing closure, signoff), CAE/CAD product engineering, and

Executive Director, Computational Systems Biology Redwood City, California, United States Revolution Medicines is a late-stage clinical oncology company developing novel targeted therapies for patients with RAS-addicted cancers. The company's R&D pipeline comprises RAS(ON) inhibitors designed to suppress diverse oncogenic variants of RAS proteins. The company's RAS(ON) inhibitors daraxonrasib (RMC-6236), a RAS(ON) multi-selective inhibitor; elironrasib (RMC-6291), a RAS(ON) G12C-selective inhibitor; zoldonrasib (RMC-9805), a RAS(ON) G12D-selective inhibitor; and RMC-5127, a RAS(ON) G12V-selective inhibitor, are currently in clinical development. As a new member of the Revolution Medicines team, you will join other outstanding professionals in a tireless commitment to patients with cancers harboring mutations in the RAS signaling pathway. The Opportunity: As an Executive Director and Head of Research Computational Biology within our Biology Function, the individual will oversee the scientific and strategic direction of systems biology research and preclinical computational biology initiatives. The individual will lead a team of computational biologists and bioinformaticians focused on acquisition, organization, and analysis of large multi-omics data sets, using both public and proprietary data sources, that will help inform treatment strategies and guide patient stratification for a growing pipeline of RAS(ON) and targeted oncology therapeutics. We are looking for an experienced leader with strong interpersonal skills and an ability to lead a strong and diverse computational biology team. Key aspects of the role include: - Strategic vision and leadership: Develop and implement a long-term strategy for research systems biology and bioinformatic activities to support a growing pipeline of RAS(ON) and novel targeted inhibitors. Lead and supervise

Cluster UI Full Stack, Engineering Lead Bengaluru, Karnataka, India; Toronto, Ontario, 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 In this role, you will be building a world class UI-based large-scale cluster management portal. This portal will act as one stop for all operations and maintenance of cerebras clusters - such as cluster bringup deployment (day0/1/2), job management, health management to name a few. Cerebras AI clusters may have 1000's of Wafer-scale accelerator systems, several 1000's of high-end servers, and several 1000's of networking ports including switches. Responsibilities - Be the primary engineering face and owner

Rebate Analyst Mumbai, India Join our team as a Rebate Analyst, where you will play a crucial role in maximizing profitability through effective rebate computation and vendor reconciliation. If you have strong analytical skills and a background in finance, we want to hear from you!

Principal ML Investigator 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 Cerebras is adding an ML team that can focus on a new ML effort that can align with existing teams. We are seeking a principal investigator who will partner with our ML leaders to formulate the new effort and to build up the new team and capabilities. This new team would coordinate with our current ML teams: Field ML, which works directly with customers, Applied ML, which builds new ML capabilities and applications for customers, and Core ML, which adapts ML algorithms to find

Full Stack LLM Engineer Toronto, Ontario, 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 seeking a versatile and experienced engineer to join our Inference Core Model Bringup team. This team is responsible to rapidly bring up state-of-the-art open-source models (like LLaMA, Qwen, etc) or customer-provided proprietary models on our Cerebras CSX systems. Success in this role requires a system-minded generalist who thrives in fast-paced bringup environments and is comfortable working across the entire Cerebras software stack. Your work will play a critical role in achieving unprecedented levels of performance, efficiency, and scalability for AI

Kernel Engineer — Scientific Computing (SPU) Redwood City | OnSite Vorticity is building the world's first Scientific Processing Unit (SPU https://pyrite9.com), a new class of silicon purpose-built to accelerate scientific computing beyond the limits of GPUs. We are designing tightly coupled software-hardware systems around applied mathematics workloads to deliver order-of-magnitude performance gains. Unlocking its full potential requires early, deep engagement from applied mathematics-driven software engineers who can translate real-world scientific workloads into executable models, kernels, libraries, and applications that inform both architecture and tooling decisions. As a Kernel Engineer, you will work at the intersection of applied mathematics, scientific computing, parallel programming, and low-level performance engineering. You will help shape how numerical kernels are implemented, optimized, and eventually mapped onto the SPU. Your work may include building early numerical kernels and libraries, developing prototype applications, and writing Python-based workload models and simulators, all to support and inform the evolving hardware and compiler stack. This requires both strong applied math fundamentals and deep low-level implementation ability. You should be comfortable moving from mathematical formulations to efficient kernels, reasoning about accuracy, stability, data movement, memory hierarchy, parallel execution, and compiler behavior along the way. This position is ideal for someone who combines strong scientific computing instincts with the low-level habits of a performance engineer. RESPONSIBILITIES - Prototyping and implementing core kernels and low-level numerical primitives for the SPU. - Translating mathematical formulations into executable, performance-relevant kernel implementations. - Analyzing and optimizing me

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