SpaceXAIβs mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the companyβs mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: The Sandbox service team at SpaceXAI builds and maintains a secure, scalable system that gives our models safe, controlled access to computational environments. This infrastructure powers critical workloads across training and product, enabling models to run code, build software, interact with tools, and even control applications with user interfaces. We provision containers and virtual machines on large-scale clusters, granting models interactive control over these remote environments. Our work spans the full stack: from orchestrating massive jobs and resource scheduling at the cluster level, to fine-tuning filesystem performance on nodes. The Sandbox service enables Grok to safely run and test code in real-time for user queries, and supports reinforcement learning in training, where models interactively explore tools ranging from compilers to productivity apps. BASIC QUALIFICATIONS: Expert knowledge of Rust, C++ or Go Familiarity with Python Deep experience with either Linux or Windows systems (familiarity with both is a strong plus) Experience with virtualisation and containerisation technologies (e.g., cgroups, KVM, gVisor, QEMU) Solid knowledge of the networking stack COMPENSATION AND BENEFITS: Β£107,000 -
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WPP is the trusted growth partner for the worldβs leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company β powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. Role Overview The Payroll Executive will be responsible for supporting end-to-end payroll operations, ensuring accurate payroll processing, statutory compliance, employee query management, and payroll reconciliations. The role requires attention to detail, strong payroll knowledge, and the ability to coordinate effectively with internal stakeholders and payroll vendors. Key Responsibilities Payroll Processing & Operations Process monthly payroll activities and ensure timely and accurate salary disbursement. Collect, validate, and compile payroll inputs including new hires, exits, salary revisions, leave data, and other employee-related changes. Prepare payroll input and reconciliation files using Excel. Verify payroll output reports received from payroll vendors, including salary registers, tax reports, and payroll summaries. Support Full & Final Settlement (F&F) processing and validation. Payroll Accounting & Reconciliations Assist in payroll account reconciliations and payroll-related general ledger validation. Support month-end payroll reporting and recon
We are now looking for a Deep Learning Software Test Development Engineer Intern! The position is in NVIDIA Deep Learning Software Quality Assurance team that defines, develops and performs tests to validate robustness and measure the performance of NVIDIAβs Deep Learning software and GPU Infrastructure for autonomous driving, healthcare, speech recognition, natural language processing, and a wide variety of other AI scenarios. This team collaborates with multiple AI product teams to develop new products; derive and improve complex test plans; and improve our workflow processes for a diverse range of GPU computing platforms. You should grow with being in the critical path supporting developers working for billion-dollar business lines as well as intimately understanding the values of responsiveness, thoroughness and teamwork. You should constantly foster and implement efficiency improvements across your domain. Join the team which is building software which will be used by the entire world! What youβll be doing: Be responsible for functionality, compatibility, and performance tests in NVIDIA AI SW stack release. Develop, maintain, and improve test automation infrastructure with using AI tools. Use AI to improve quality and productivity across QA End-to-End workflow. Work with development teams to triage issues, root cause analysis, verify fixes, define new tests, improve test plans. What we need to see: Pursuing MS or higher degree in CS/EE/CE or a related field. Proven success in leveraging AI tools to significantly improve efficiency, streamline workflows or enhance process automation. Good python, C++ programming skillset, Linux knowledge is required. Experience in software development with popular AI model
Deep Learning Software Engineering Intern, Test Development - 2027 β Shanghai, China. Apply via Workday.
Deep Learning Software Engineering Intern, Test Development - 2027 β Shanghai, China. Apply via Workday.
Deep Learning Performance Architect β 2 Locations. Apply via Workday.
NVIDIA is leading company of AI computing. At NVIDIA, our employees are passionate about AI, HPC , VISUAL, GAMING. Our SA team is more focusing to bring NVIDIA new technology into difference industries. We help to design the architecture of AI computing platform, analysis the AI and HPC applications to deliver our value to customers, focusing on defining and solving computational challenges in LLM inference and training acceleration, as well as network communication and data transfer optimization. What You'll Be Doing: Contribute to the development of open-source inference frameworks such as SGLang and vLLM, including feature and operator development, performance optimization, and model support, in collaboration with the community. Develop and optimize KV cache offloading frameworks for LLM workloads, supporting multi-level cache offloading and reuse across CPU, SSD, and remote storage to improve inference efficiency. (Team project: FlexKV) Drive R&D on compute performance in distributed training, and explore methods and technologies for performance optimization. Study computational challenges in machine learning systems, identify common needs and bottlenecks, and build example code, acceleration libraries, or frameworks accordingly. What We Need to See: Over 5 years working experience in the technology industry, with masterβs degree or above in computer science, mathematics, electrical engineering, automation, or related fields. Strong interest in accelerated computing, parallel computing, and heterogeneous computing, with the motivation to explore these areas in depth. Solid programming skills, with a good understanding of data structures and computer systems fundamentals. Strong learning agil
Job Details: Job Description: The Role and Impact As a Sr Deep Learning Hardware Verification Engineer, you will play a pivotal role in shaping the future of AI hardware by validating and optimizing next-generation NPU silicon solutions. In this role you will join the NPU Hardware Pre-Silicon Validation team working closely with design engineers, model engineers and AI architects to validate components of the next generation NPU IP portfolio, your contributions will directly shape Intel's advancements in AI technologies. Your responsibilities will include: β’ Functional Verification of complex digital design block(s) on the latest generations of Intel's NPU AI accelerators. β’ Architect, development and implementation of verification environments from initial planning through the validation lifecycle to review and signoff. β’ Development of test plans and test cases. β’ Implementation of random test generators, high level transactional models, bus functional models (BFMs), functional/formal constraints, checkers and scoreboards, coverpoints/covergroups and SVA properties. β’ Implementation of software based testcases for functional and performance based testing of the NPU AI accelerators. β’ Collaborate with cross-functional teams to analyses and address next-generation AI requirements, influencing the AI product roadmap. Leixlip is the primary location for this position, however, we offer some flexibility to support your work/life balance arrangements. Business group The Artificial Intelligence and Deep Learning team drives innovation in AI hardware development, aligning with Intel's mission to deliver world-class solutions in the AI domain. With a focus on building state-of-the-art hardware that supports cutting-edge AI models, the team collaborates across Intel to en
Senior Deep Learning Scientist, Multimodal Agentic RL β 2 Locations. Apply via Workday.
Senior Deep Learning Engineer, Accuracy Evaluation β 5 Locations. Apply via Workday.
NVIDIA is leading groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU -- our invention -- serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables groundbreaking creativity and discovery, and powers inventions that were once considered science fiction, including artificial intelligence to autonomous cars. We are the GPU Communications Libraries and Networking team at NVIDIA. We build communication libraries like NCCL, NVSHMEM, and UCX that are crucial for scaling Deep Learning and HPC. We're seeking a Senior Software Architect to help co-design next-gen data center platforms and scalable communications software. DL and HPC applications have a huge compute demands and already run at scales of up to tens of thousands of GPUs. GPUs are connected with high-speed interconnects (e.g. NVLink, PCIe) within a node and with high-speed networking (e.g. InfiniBand, Ethernet) across nodes. Efficient and fast communication between GPUs directly impacts end-to-end application performance. This impact continues to grow with the increasing scale of next generation systems. This is an outstanding opportunity to advance the state-of-the-art, break performance barriers, and deliver platforms the world has never seen before. Are you ready to build the new and innovative technologies that will help realize NVIDIA's vision? What you will be doing: Investigate opportunities to improve communication performance by identifying bottlenecks in today's systems. Design and implement new communication technologies to accelerate AI and HPC workloads. Explore innovative solutions in HW and SW for our next generation platforms as part of co-design efforts involving GPU, Networking, and SW architects. Build proofs-of-concept, conduct experiments,
Artificial Intelligence Research Intern - Deep Learning β Taiwan, Taipei. Apply via Workday.
NVIDIA 2027 New College Graduate: Deep Learning and High-Performance Computing Engineering - China β 3 Locations. Apply via Workday.
Role Purpose: The Machine Learning Engineer IV will play a critical role in advancing Jumio's Fraud team's mission to develop and enhance state-of-the-art solutions for fraud detection for ID verification purposes. This role is essential for ensuring the highest standards of security and user verification through the application of advanced machine learning and deep learning techniques, ultimately contributing to Jumio's leadership in the online identity verification, eKYC, and AML solutions market Role Value: As a Machine Learning Engineer IV at Jumio, you will have the opportunity to significantly impact the security and user experience of our ID verification solutions. Your expertise in deep learning and computer vision will drive the development of innovative algorithms that keep Jumio at the forefront of the industry. By deploying and maintaining these models in production, you will ensure the robustness and reliability of our solutions, supporting our clients across diverse industries such as Financial Services, Travel, Sharing Economy, Fintech, and Gaming. Your contributions will be pivotal in maintaining Jumio's reputation as the leading provider of online identity verification solutions, helping to meet the growing demand for secure and seamless user verification globally. Example Responsibilities . Develop, maintain, and own key fraudulent CV models of Jumio, which shapes the whole fraud product offering of Jumio. Design and implement machine learning, deep learning, classical CV focused on fraud detection. Research to support the deployment of the advanced algorithms. Deploy models as AWS SageMaker endpoints or directly onto devices. Stay updated with the latest advancements in machine learning, deep learning, and computer vision by engaging with academic papers and attending industry conferences. Work collaboratively with other engineers and product managers in an Agile development environment. Experience and Qualifications Bach
About the Role: The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding and ads optimization that shape the future of streaming. We are seeking a highly skilled Senior Machine Learning Engineer to contribute to transformative projects in video personalization. In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy. As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross-functional teams to develop and optimize machine learning-driven solutions. This is a hybrid role in our Toronto office. What You'll Do: Design, develop, and implement recommendation systems and algorithms for a global audience Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences. Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement Your Background: 3+ years of industry experience building production Machine Learning systems BS, MSc, or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks Proficiency in building and deploying full-stack machine learning pipelines: data e
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