Neural Magic jobs

Machine Learning Engineer - Perception Foster City, CA The Perception team at Zoox is at the forefront of leveraging GenAI to create synthetic data, unlocking scalable training and evaluation for our autonomous system's perception and entire stack. As a Generative AI Engineer, you will develop and train cutting-edge models for sensor-level scenario generation, utilizing world models and radiance fields techniques with large-scale proprietary data. This role directly impacts the productivity, safety, and capabilities of Zoox's autonomous system by validating algorithms in real-world conditions. The Perception team at Zoox is at the forefront of leveraging GenAI to create synthetic data, unlocking scalable training and evaluation for our autonomous system's perception and entire stack. As a Generative AI Engineer, you will develop and train cutting-edge models for sensor-level scenario generation, utilizing world models and radiance fields techniques with large-scale proprietary data. This role directly impacts the productivity, safety, and capabilities of Zoox's autonomous system by validating algorithms in real-world conditions. In this role, you will: - Design, develop, train and evaluate multi-sensor fusion based deep learning models to understand obstacles and environmental context - Understand and curate real and synthetic datasets to improve our models - Perform latency optimization and deploy models to our robot fleet - Build a deep understanding of Perception gaps and behavioral issues around difficult obstacle types in order to help plan and prioritize our work - Collaborate with Prediction/Planner team to deploy fully autonomous vehicles in environments with difficult and rare obstacles, extreme weather conditions, and complex

Senior Deep Learning Engineer (Perception) Sausalito The Job: We are seeking an exceptional and highly motivated Deep Learning Engineer to join our fast-moving and innovative team. In this role, you will leverage your expertise to research, develop, and deploy cutting-edge perception algorithms for our next-generation autonomous systems. You will play a pivotal part in building the "eyes" of our technology, enabling it to robustly perceive and understand the surrounding world. This is a hands-on, systems-level role where you will bridge fundamental research and real-world deployment, tackling complex challenges. As a key early member of our technical team, you will have significant ownership and the opportunity to directly shape our product's perception capabilities. What You'll Do: Algorithm development: Research, design, and implement advanced deep learning algorithms for core perception tasks, such as 2D/3D object detection, semantic segmentation, tracking, and classification. Multimodal sensor fusion: Develop and optimize algorithms to fuse data from multiple sensor modalities, including cameras, LiDAR, and radar, to build a robust and comprehensive perception system. Data-centric development: Take a rigorous, data-driven approach to model development. This includes designing training and validation pipelines, curating large-scale datasets, and prioritizing data collection and labeling efforts. System integration: Work cross-functionally with embedded, hardware, and systems engineers to seamlessly integrate perception software into the larger autonomous stack. Performance analysis and debugging: Analyze logged field data to identify performance bottlenecks and edge cases, and rapidly iterate on solutions to improve model accuracy and robustness in challenging real-world conditions. Stay current on research: Keep abreast of

Consultant - Middleware Remote Malaysia posted: Posted 30+ Days Ago

Software Development Engineer AI/ML, Inference Serving, AWS Neuron Cupertino, California, USA AWS Neuron is the software stack powering AWS Inferentia and Trainium machine learning accelerators, designed to deliver high-performance, low-cost inference at scale. The Neuron Serving team develops infrastructure to serve modern machine learning models-including large language models (LLMs) and multimodal workloads-reliably and efficiently on AWS silicon. We are seeking a Software Development Engineer to lead and architect our next-generation model serving infrastructure, with a particular focus on large-scale generative AI applications. Key job responsibilities * Architect and lead the design of distributed ML serving systems optimized for generative AI workloads * Drive technical excellence in performance optimization and system reliability across the Neuron ecosystem * Design and implement scalable solutions for both offline and online inference workloads * Lead integration efforts with frameworks such as vLLM, SGLang, Torch XLA, TensorRT, and Triton * Develop and optimize system components for tensor/data parallelism and disaggregated serving * Implement and optimize custom PyTorch operators and NKI kernels * Mentor team members and provide technical leadership across multiple work streams * Drive architectural decisions that impact the entire Neuron serving stack * Collaborate with customers, product owners, and engineering teams to define technical strategy * Author technical documentation, design proposals, and architectural guidelines A day in the life You'll lead critical technical initiatives while mentoring team members. You'll collaborate with cross-functional teams of applied scientists, system engineers, and product managers to architect and deliver state-of-the-art inference capabilities. Your day might involve: * Leading

Specialist Solution Architect Tokyo posted: Posted 9 Days Ago

Staff Inference ML Runtime Engineer 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 Systems is dedicated to enabling our fast generative inference solution through simple APIs powered by a distributed runtime that runs on large clusters of our own hardware. Our mission is to empower enterprises, developers, and researchers to unlock the full potential of our platform, leveraging its performance, scalability, and flexibility. The team works closely with cross-functional groups, including compiler developers, cluster orchestrators, ML scientists, cloud architects, and product teams, to deliver high-impact

Senior Consultant - Ansible Singapore posted: Posted 30+ Days Ago

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

Principal Data Scientist 2 Locations posted: Posted Today

Executive Policy Engagement Lead, DeepMind London, UK In this role, you will be an experienced leader to co-design and scale DeepMind's Executive Policy Engagement function. You will help to set and drive the strategy for how DeepMind's executives build trust with governments and policymakers. You will own long-term engagement plans, brief and staff our executives for high-stakes events, and help to build an executive policy engagement function. You are an autonomous leader with advisory experience, operating expertly at the intersection of policy, communications, and executive management. You will collaborate closely and build trust with leaders in partner teams, including Communications and multiple executive offices. Artificial intelligence will be one of humanity's most transformative inventions. At DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority. We are pushing the boundaries across multiple domains. Our global teams offer learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort. Partner with leadership to build the executive policy engagement function. Own, design, and execute bespoke, long-term engagement strategies for our growing executive portfolio. Serve as the primary on-the-ground counsel for executives during international travel, providing real-time political insights and navigating stakeholder dynamics at major global forums. Draft researched briefing materials, speech content, and policy narratives to ensure

Senior Architect Remote Malaysia posted: Posted 17 Days Ago

Senior Principal Machine Learning Engineer, vLLM Boston posted: Posted 24 Days Ago

Software Engineer, Telco Raleigh posted: Posted 25 Days Ago

Junior Solution Architect- Openshift Singapore posted: Posted Yesterday

AI Solution Specialist, ANZ (Sydney/Melbourne-based) 3 Locations posted: Posted 13 Days Ago

Sr. SDM, AI Inference Technology, Neuron SDK Seattle, Washington, USA AWS Utility Computing (UC) provides product innovations - from foundational services such as Amazon Elastic Compute Cloud (EC2), to new product innovations that continue to set AWS's services and features apart in the industry. Come develop inference acceleration for AWS Neuron, the complete software stack for Trainium, Amazon's custom cloud-scale machine learning accelerators that power the latest AI models As the Sr. SDM for the Inference Technology Team, you will lead a strong team of managers and engineers to build fundamental inference technology building blocks and libraries to enable AI developers to optimize model for inference on Trainium and Inferentia devices. You will be responsible for the full development life cycle of inference library and feature development, including reliability and scalability. You will develop the Neuronx_Distributed Inference Libraries and contribute to other popular open source Inference Libraries, enabling customers to optimize LLMs, multimodal, and generative models. The ideal candidate will have an established background in delivering AI feature support for demanding, fast-changing priorities or delivering high-performance models using distributed inference libraries. The ideal candidate should have a strong technical ability to understand and manage a vertically integrated system stack that consisting of hardware, frameworks, and workflows. A day in the life You will work with the executive leadership and other senior management and technical leaders to define product directions and deliver them to customers. We build massive-scale distributed training and inference solutions, developing the full stack of software, servers and

Agile Development Coach Tokyo posted: Posted 25 Days Ago

Sr. ML Kernel Performance Engineer, AWS Neuron, Annapurna Labs Cupertino, California, USA The Annapurna Labs team at Amazon Web Services (AWS) builds AWS Neuron, the software development kit used to accelerate deep learning and GenAI workloads on Amazon's custom machine learning accelerators, Inferentia and Trainium. The Acceleration Kernel Library team is at the forefront of maximizing performance for AWS's custom ML accelerators. Working at the hardware-software boundary, our engineers craft high-performance kernels for ML functions, ensuring every FLOP counts in delivering optimal performance for our customers' demanding workloads. We combine deep hardware knowledge with ML expertise to push the boundaries of what's possible in AI acceleration. The AWS Neuron SDK, developed by the Annapurna Labs team at AWS, is the backbone for accelerating deep learning and GenAI workloads on Amazon's Inferentia and Trainium ML accelerators. This comprehensive toolkit includes an ML compiler, runtime, and application framework that seamlessly integrates with popular ML frameworks like PyTorch, enabling unparalleled ML inference and training performance. As part of the broader Neuron Compiler organization, our team works across multiple technology layers - from frameworks and compilers to runtime and collectives. We not only optimize current performance but also contribute to future architecture designs, working closely with customers to enable their models and ensure optimal performance. This role offers a unique opportunity to work at the intersection of machine learning, high-performance computing, and distributed architectures, where you'll help shape the future of AI acceleration technology This is an opportunity to work on cutting-edge products at

Cloud Architect Mexico City posted: Posted 5 Days Ago

Director, Solution Architecture Kuala Lumpur posted: Posted 30 Days Ago

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