Neural Magic jobs

Machine Learning: Whole-Body Control San Francisco The Bot Company We're building a helpful robot for every home. We're a small team of engineers, designers, and operators based in San Francisco. Our team comes from Tesla, Cruise, OpenAI, Google, Pixar, and many other great companies. In the past we've shipped to hundreds of millions of users and know what it takes to build amazing products and experiences. Our team is deliberately lean to promote rapid decision making and do away with bureaucracy and hierarchy. Everyone is an IC and is empowered with massive scope, radical ownership, and direct responsibility. We work across the stack with a culture built for rapid iteration and fast execution. What we look for in all candidates All roles at The Bot Company demand extreme sharpness and the ability to move fast in high-intensity environments. Throughout the process, we expect candidates to demonstrate: - Exceptional mental acuity: you think quickly, learn instantly, and reason across unfamiliar domains. - Engineering curiosity: you naturally dig into how systems work, even outside your specialty. - High performance mindset: you move fast, handle ambiguity, and excel when the environment is demanding. Machine Learning: Whole-Body Control We are building high-performance whole-body controllers that produce robust, agile motion and manipulation in the real world. You will train low-level control policies in simulation and own the stack from environment design to large-scale training and sim-to-real deployment. What You'll Do - Train whole-body policies for locomotion, manipulation, and coordinated motion. - Build scalable simulation environments

Senior Resource Deployment Specialist Melbourne posted: Posted 21 Days Ago

Research Scientist, Robotics, DeepMind Cambridge, MA, 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 Google 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. In this role, you will focus on building foundation models, such as advanced vision-language-action (VLA) models, which combine Gemini's world understanding with physical actions to provide direct robotic control. These include Gemini Robotics, our most advanced Gemini model for the physical world, and Gemini Robotics On-Device, our fastest Gemini model that functions without a data network. These models allow robots to perform a broad range of tasks, respond interactively to their environment, achieve high dexterity, and reason over long, multi-step sequences. Beyond model building, we are committed to advancing general-purpose robotics, specifically in areas like agentic reasoning, real-world understanding, action generalization, human-robot interaction, dexterity, whole-body control, and continual learning. To deploy these innovations at scale, you will partner with key robotics companies to bring this intelligence to the physical world across a broad array of applications. Artificial intelligence will be one of humanity's most transformative

Principal Engineer, AI Inference Reliability Remote, California, United States; 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. In late 2024, we launched Cerebras Inference, the fastest Generative AI inference service in the world, over 10 times faster than GPU-based hyperscale cloud inference. Since launch, we've scaled to meet the surging demand from AI labs, enterprises, and a thriving developer community. In October 2025, we announced our series G funding, raising $1.1 billion USD to accelerate the expansion of our products and services to meet global AI demand. About the team The Cerebras Inference team's mission

Technical Translator, Korean Language Remote Australia posted: Posted Today

Principal Applied Scientist, Neuro-Symbolic AI Labs Boston, Massachusetts, USA We are looking for researchers who aim to build super-intelligent AI systems that leverage proof assistants to guide learning and reasoning. Our neuro-symbolic AI technology is applied across a wide range of science and engineering domains within Amazon, and you will join the team at the forefront of this research. As a Principal Applied Scientist, you will play a pivotal role in shaping the definition, vision, and development of product features from beginning to end. You will: - Define and implement new neuro-symbolic applications that employ scalable and efficient approaches to solve complex problems. - Work in an agile, startup-like development environment, where you are always working on the most important stuff. - Deliver high-quality scientific artifacts. About the team We work closely with academia. Our team includes an Amazon Scholar in mathematics, and we maintain active research collaborations with faculty at leading CS departments (MIT, Berkeley, CMU). Basic Qualifications: - Experience programming in Java, C++, Python or related language - Experience with leading experienced scientists as well as having a record of developing junior members from academia or industry to a career track in a business environment - PhD, or Master's degree and 8+ years of applied research experience Preferred Qualifications: - 10+ years of relevant work in industry or academia experience - Experience creating novel algorithms and advancing the state of the art - Have peer-reviewed scientific contributions in premier journals and conferences Amazon is an equal opportunity employer

Deep Learning Engineer Seattle, WA The Carbon Robotics LaserWeeder™ leverages advanced robotics, computer vision, AI/deep learning, and lasers to eliminate weeds with sub-millimeter accuracy-all without herbicides. This innovative solution reduces environmental impact, promotes soil health, and helps farmers address labor shortages and rising costs. Designed in Seattle and built at our cutting-edge manufacturing facility in Richland, Washington, the LaserWeeder is setting a new standard for automated weed control. With $157 million in funding from prominent investors such as BOND, NVentures (NVIDIA's venture arm), Anthos Capital, Fuse Venture Capital, Ignition Partners, Revolution, Sozo Ventures, and Voyager Capital , Carbon Robotics is driving innovation. As a no-nonsense team with a bias for action, we take pride in executing our ideas. Whether it's designing transformative technology or visiting farms to ensure our products are reliable and safe, we do whatever it takes to deliver for our customers. Working here means tackling big problems with big impact. You'll find opportunities to grow professionally, solve complex challenges, and make meaningful contributions to a mission that matters. At Carbon Robotics, we trust our team to act independently and make practical, real-world decisions. Join us as we innovate, execute, and build the future of farming together. YouTube | X | Instagram | LinkedIn | News Deep Learning Engineer As a Deep Learning Engineer at Carbon Robotics, you will contribute to designing, developing, and deploying novel deep learning systems that power our autonomous laser weeding robots in the field. What You'll Do - Lead the design and execution

Training Experience Specialist 2 Locations posted: Posted 9 Days Ago

Senior Software Engineer- Hyperfleet -Maestro Raleigh posted: Posted Yesterday

Partner Sales Account Manager – AI Ecosystem & Strategic Partnerships Tokyo posted: Posted 11 Days Ago

Robotics Hardware Industrialization Engineer, DeepMind Mountain View, CA, USA Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration. The Embodied Systems team is the new hardware-centric group within Deepmind Robotics. Our mission is to accelerate AI research in the physical domain through the world's most advanced robotics systems. You will be joining on the ground floor of our hardware operations, meaning your fingerprints will be on the processes, products and relationships that we forge. As a mechanically-capable Industrialization Engineer, you will join our robotic Engineering Operations team within Deepmind. The Industrialization Engineer bridges the gap between robotics research goal and scalable data collection in a laboratory environment. You will transform advanced research testing concepts into actionable designs and processes for our data collection humanoid laboratories. You will require collaboration with Research and Development, facilities, supply chain, and engineering teams to optimize robot operations, reduce costs, and optimize system reliability. You will be the first point of contact for any test cell design-related topics, and an authority on process control and DFM (Design For Manufacture)/DFX (Design For excellence) approaches. You will work with the engineering and development teams to define the functional hardware and processes that lead to a highly productive and scalable laboratory environment where a multitude of humanoid robots are operating,

Software Engineer- AI/ML, AWS Neuron Cupertino, California, USA AWS Neuron is the complete software stack for the AWS Inferentia and Trainium cloud-scale machine learning accelerators and the Trn1 and Inf1 servers that use them. This role is for a software engineer in the Machine Learning Applications (ML Apps) team for AWS Neuron. This role is responsible for development, enablement and performance tuning of a wide variety of ML model families, including massive scale large language models like LLama4, Mixtral, DBRX and beyond, as well as stable diffusion, Vision Transformers and many more. The Distributed training team works side by side with chip architects, compiler engineers and runtime engineers to create , build and tune distributed training solutions with Trainium. Experience training these large models using Python is a must. FSDP, Deepspeed and other distributed training libraries are central to this and extending all of this for the Neuron based system is key. Key job responsibilities This role will help lead the efforts building distributed training support into Pytorch and Jax using XLA and the Neuron compiler and runtime stacks. This role will help tune these models to ensure highest performance and maximize the efficiency of them running on the customer AWS Trainium . Strong software development and ML knowledge are both critical to this role. About the team About Us Inclusive Team Culture Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over

Sales Specialist 3 3 Locations posted: Posted 30+ Days Ago

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

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

Sales Account Executive Amsterdam - MSO posted: Posted 9 Days Ago

UI Design Engineer 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 BCI Applications Team is responsible for building Telepathy.app-software which enables people with paralysis to use computing devices with precision and ease, via thought alone. Our team spans a wide range of disciplines, from neuroscience and machine learning to software engineering and interface design. Job Description: We're looking for an experienced UI Design Engineer to conceptualize, prototype, and ship novel computing interfaces tailored for BCI. Our ideal candidate will possess the following qualities: - Passion to explore an open-ended, multi-disciplinary, constrained space where design choices are informed by neural structure, model architecture, radio bandwidth, and more. For instance, a slight difference in an animated spring coefficient can change perceptual response time, shifting the alignment of labels and the performance of our decoders. You will actively collaborate with domain experts within and outside the team to understand these constraints and design your way around them - An intuitive sense for what level of fidelity to reach for when navigating this space, be it a conversation, a rough sketch, or a testable prototype - Excitement to work within and push the boundaries of an entirely new medium of interaction without the traditional sensory feedback of existing physical input devices (e.g., the kinetic friction

RHEL Sales Specialist Buenos Aires posted: Posted 17 Days Ago

Hands-On RHEL Architect - Consulting Be'er Sheva posted: Posted 19 Days Ago

Senior App Dev Consultant Tokyo posted: Posted 22 Days Ago

Senior Applied Scientist, Neuro-Symbolic AI Labs Boston, Massachusetts, USA We are looking for researchers who aim to build super-intelligent AI systems that leverage proof assistants to guide learning and reasoning. Our neuro-symbolic AI technology is applied across a wide range of science and engineering domains within Amazon, and you will join the team at the forefront of this research. As an Applied Scientist here, you will play a pivotal role in shaping the definition, vision, and development of product features from beginning to end. You will: * Define and implement new neuro-symbolic applications that employ scalable and efficient approaches to solve complex problems. * Work in an agile, startup-like development environment, where you are always working on the most important stuff. * Deliver high-quality scientific artifacts. About the team We work closely with academia. Our team includes an Amazon Scholar in mathematics, and we maintain active research collaborations with faculty at leading CS departments (MIT, Berkeley, CMU). Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and

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