Neural Magic jobs

Account Solution Architect Brasilia - MSO posted: Posted 30+ Days Ago

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

Commercial Sales Program Manager Raleigh posted: Posted 24 Days Ago

Market Development Representative (m/f/d) Zurich - MSO posted: Posted Today

Electrical Engineer 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. Responsibilities - Lead printed circuit board design through all development stages: from definition to implementation, bring-up, qualification, and production release. - Full responsibility for electrical specification, schematic design, components selection, and layout considerations. - Extensive lab bring-up and debugging, including developing automated benchtop setups for board characterization. - Collaborate with various design and operations teams: manufacturing operations & test engineering, supply chain, ASIC, mechanical, signal integrity, power delivery, layout, embedded & diagnostic, etc. Skills & Qualifications - B.S.c, M.S.c, or Ph.D. degree in electrical engineering, or equivalent experience.

Technical Account Manager 2 Locations posted: Posted 30+ Days Ago

Principal PMT-ES - AI/ML Training, Annapurna Labs Cupertino, California, USA AWS Trainium is deployed at scale, with millions of chips in production, used for training and inference of frontier models. AWS Neuron is the software stack for Trainium, enabling customers to run deep learning and generative AI workloads with optimal performance and cost efficiency. AWS Neuron is hiring a Principal Technical Product Manager to define and drive product strategy for training software on Trainium. This includes distributed training libraries, post-training workflows (RLHF, DPO, fine-tuning), reinforcement learning frameworks, and training performance optimization. Your mission is to enable researchers and operators to train frontier models at scale on Trainium, from single-node experimentation to distributed training across thousands of nodes. You will be the champion inside AWS for frontier model builders pushing the bounds of scale and resilience for current and emerging training paradigms. You will work with customers inside and outside the company to identify key improvements and stay ahead of the training landscape. You will define how Neuron supports the training AI/ML ecosystem and what tools customers will use for their training workflows on Trainium. To be successful, you will partner with engineering teams building training libraries and distributed training infrastructure, applied scientists developing optimization techniques, and PMs responsible for compiler, runtime, NKI, and infrastructure. You will develop deep knowledge of AI/ML training architectures, distributed training systems, model parallelism strategies, and training performance optimization to effectively define product strategy and make informed technical decisions. The Ideal Candidate The ideal candidate will

Strategic Accounts Manager Jakarta - MSO posted: Posted 30+ Days Ago

Sr. Machine Learning - Compiler Engineer III, AWS Neuron, Annapurna Labs Cupertino, California, USA The Product: AWS Machine Learning accelerators are at the forefront of AWS innovation and one of several AWS tools used for building Generative AI on AWS. The Inferentia chip delivers best-in-class ML inference performance at the lowest cost in cloud. Trainium will deliver the best-in-class ML training performance with the most teraflops (TFLOPS) of compute power for ML in the cloud. This is all enabled by cutting edge software stack, the AWS Neuron Software Development Kit (SDK), which includes an ML compiler, runtime and natively integrates into popular ML frameworks, such as PyTorch, TensorFlow and MxNet. AWS Neuron and Inferentia are used at scale with customers like Snap, Autodesk, Amazon Alexa, Amazon Rekognition and more customers in various other segments. The Team: As a whole, the Amazon Annapurna Labs team is responsible for silicon development at AWS. The team covers multiple disciplines including silicon engineering, hardware design and verification, software and operations. The AWS Neuron team works to optimize the performance of complex neural net models on our custom-built AWS hardware. More specifically, the AWS Neuron team is developing a deep learning compiler stack that takes neural network descriptions created in frameworks such as TensorFlow, PyTorch, and MXNET, and converts them into code suitable for execution. As you might expect, the team is comprised of some of the brightest minds in the engineering, research, and product communities, focused on the ambitious goal of creating a toolchain

Technical Account Manager - OpenShift 3 Locations posted: Posted Today

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

Strategic Accounts Manager, FSI Mumbai posted: Posted 30+ Days Ago

Junior or Software Engineer - Virtualization Cloud Team (Brno Office, Czech Republic) Brno - Tech Park Brno - C posted: Posted 18 Days Ago

Senior Engineering Partner Manager Raleigh posted: Posted 21 Days Ago

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

Infrastructure Telco Architect 2 Locations posted: Posted 7 Days Ago

Staff AI/ML Architect, Embodied AI Sunnyvale, CA, United States Company Description: It started with a simple idea: what if surgery could be less invasive and recovery less painful? Nearly 30 years later, that question still fuels everything we do at Intuitive . As a global leader in robotic-assisted surgery and minimally invasive care , our technologies-like the da Vinci surgical system and Ion -have transformed how care is delivered for millions of patients worldwide. We're a team of engineers, clinicians, and innovators united by one purpose: to make surgery smarter, safer, and more human. Every day, our work helps care teams perform with greater precision and patients recover faster, improving outcomes around the world. The problems we solve demand creativity, rigor, and collaboration. The work is challenging, but deeply meaningful-because every improvement we make has the potential to change a life. The Future Forward organization is Intuitive's advanced concepts group. We explore emerging technologies, prototype next-generation solutions, and build software experiences that shape the future of robotic-assisted surgery. If you're ready to contribute to something bigger than yourself and help transform the future of healthcare , you'll find your purpose here. Job Description: Primary Function of Position We are building advanced augmented dexterity capabilities for next-generation robotic platforms. As a Staff AI/ML Architect, you will own the end-to-end architecture of our applied-AI system: a hierarchical, multimodal stack in which a high-level model interprets sensory observations and produces structured intent, and a low-level policy turns that intent into precise, safe, real-time

Senior Software Engineer Bangalore - Carina posted: Posted 30+ Days Ago

Machine Learning Engineer Intern South San Francisco, California, United States About Neuralink: We are creating devices that enable a bi-directional interface with the brain. These devices allow us to restore movement to the paralyzed, restore sight to the blind, and revolutionize how humans interact with their digital world. Team Description: The Brain Computer Interface (BCI) Applications Team is responsible for delivering a product that gives people with paralysis the ability to control computers, phones, gaming consoles, and robotic arms with their minds at the same speed and functionality level as able-bodied people can. Furthermore, the team is focused on restoring speech for mute individuals and enabling direct, natural silent communication with AI agents. In this role, you'll work with neuroscientists, physicians, software engineers, and electrical engineers to develop the next-generation human-ready Brain-Computer Interface (BCI). Job Description and Responsibilities: We are hiring a Machine Learning Engineer Intern to develop novel neural decoders to increase control speed and accuracy, improve reliability, and expand functionality of BCIs. You will play a critical role in developing machine learning solutions and driving the successful execution of projects to achieve mission critical goals. You'll work with cross-functional teams to design new BCI functionalities and novel computer user interfaces. Required Qualifications: - Evidence in delivering high-impact projects either in academia or industry - Prior experience designing and building Machine Learning models - Deep understanding of machine learning concepts and fundamentals - Experience in analyzing complex datasets, driving insights, and communicating results in a simple and clear way

Senior Information Systems Engineer Pune posted: Posted 9 Days Ago

Research Scientist, Manipulation for Robotics, DeepMind Mountain View, CA, USA We believe there are many problems in the world in which robotics could play a significant role in making it easier, faster and safer for people to get things done. We're looking for roboticists, designers, hardware and software engineers to help us explore these possibilities, develop breakthrough technologies, and build new products that could help millions of people. At DeepMind Robotics, we are pioneering the integration of AI into the physical world to power an era of physical agents. By enabling robots to perceive, plan, think, use tools, and act, we empower them to solve increasingly tasks. Research Scientists work on stimulating range of projects including: inventing algorithms and prototype applications, working with real robots in the lab and outside the lab managing real world use cases. Research Scientists work in large collaborative teams to make breakthroughs to advance Robotics AI. We believe large foundation models will transform general purpose Robotics like with our Gemini Robotics models. This role will involve working with a multi-functional team that builds the future of robotics. You will be working on enabling robots to perform human level manipulation, using frontier robotics models for general purpose dexterous tasks reaching human level performance on real world applications. You will be working in a world-leading robotics research team and collaborate with other teams within DeepMind. Artificial intelligence will be one of humanity's most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary

Strategic Accounts Manager - Telco Tokyo posted: Posted 21 Days Ago

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,

Machine Learning Compiler Engineer Cupertino, California, USA The Product: Amazon's Machine Learning accelerators are at the forefront of our innovation and one of several Amazon's tools used for building Generative AI on Amazon. The Inferentia chip delivers best-in-class ML inference performance at the lowest cost in cloud. Trainium will deliver the best-in-class ML training performance with the most teraflops (TFLOPS) of compute power for ML in the cloud. This is all enabled by cutting edge software stack, the Amazon Neuron Software Development Kit (SDK), which includes an ML compiler, runtime and natively integrates into popular ML frameworks, such as PyTorch, TensorFlow and MxNet. Amazon Neuron and Inferentia are used at scale with customers like Snap, Autodesk, Amazon Alexa, Amazon Rekognition and more customers in various other segments. The Team: As a whole, the Amazon Annapurna Labs team is responsible for silicon development at Amazon. The team covers multiple disciplines including silicon engineering, hardware design and verification, software and operations. The Amazon Neuron team works to optimize the performance of complex neural net models on our custom-built Amazon hardware. More specifically, the AWS Neuron team is developing a deep learning compiler stack that takes neural network descriptions created in frameworks such as TensorFlow, PyTorch, and MXNET, and converts them into code suitable for execution. As you might expect, the team is comprised of some of the brightest minds in the engineering, research, and product communities, focused on the ambitious goal of creating a toolchain that will provide a quantum leap in