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Engineer 4 Jobs

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Experienced Low Observables Mission Systems Integration Engineer Company: The Boeing Company We are seeking a Low Observables (LO) Design & Integration Engineer to support design and analysis activities for stealth/low-signature systems. The engineer will perform LO material and structure design, electromagnetic analysis, integration and test support, data processing, and technical reporting. The role requires practical experience with LO materials and technologies, solid electromagnetics knowledge, and hands-on expertise with computational electromagnetic (CEM) solvers used to design and optimize LO solutions. Key Responsibilities Perform design and analysis tasks for LO materials, coatings, treatments, and structural treatments to minimize radar, infrared, and other signatures. Develop and validate LO integration concepts for aircraft/vehicle structures and subsystems, including manufacturability and testability considerations. Use CEM solvers to model, simulate, and optimize LO components and systems (e.g., surface treatments, RAM, apertures, seams, RAM-structure interactions). Perform sensitivity studies and trade-offs across materials, geometry, and integration approaches to meet system-level LO requirements. Process and analyze measured test data from laboratory and flight/field tests; compare test results to simulation and iterate designs. Produce technical documentation: detailed analysis reports, integration guidance, test plans, and summaries suitable for engineering and program management audiences. Communicate technical results and recommendations to multidisciplinary teams and support design reviews. Support manufacturing and test engineering to ensure LO design intent is preserved through fab

pythonrecruitment
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Hp
πŸ“ Texasβ€’ $147.1K – $230.9K/yr
1mo ago

Principal Embedded Firmware and Software Engineer Description - We are seeking a Principal Embedded Firmware & Software Engineer to lead the design, development, and debugging of embedded software and firmware for computer systems. In this role, you will combine deep, hands-on engineering expertise with system-level technical leadership to ensure seamless integration between software and hardware components, delivering reliable and efficient system performance. You will collaborate closely with cross-functional teams including hardware engineers, software developers, QA, and product managers to bring high-quality products to market. Responsibilities Provide technical leadership for the architecture, development, security, integration, debugging, validation, and deployment of embedded firmware and software including BIOS/UEFI, EFI applications and drivers, embedded controllers, and RTOS-based systems. Analyze hardware and system architectures to define firmware requirements, dependencies, interfaces, integration strategies, and validation approaches. Troubleshoot and resolve firmware issues by designing and implementing enhancements, updates, and programming changes across firmware subsystems. Define and drive firmware integration, verification, and validation strategies, including automated testing, regression testing, and continuous integration . Develop and improve engineering tools and automation using Python and other appropriate technologies for development, debugging, testing, analysis, and validation. Advance CI/CD and DevSecOps practices for embedded development to improve engineering velocity, quality, traceability, and release confidence. Evaluate and apply AI-assisted software development and engineering tools where they can improve developer productivity,

pythongitlinux
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NVIDIA is seeking a highly enthusiastic and motivated Verification Engineer to verify the design and implementation of the next generation of control subsystems for the world’s leading GPUs. This position offers the opportunity to have real impact in a dynamic, technology-focused company impacting product lines ranging from consumer graphics to self-driving cars and the growing field of artificial intelligence. We have crafted a team of outstanding people stretching around the globe, whose mission is to push the frontiers of what is possible today and define the platform for the future of computing. At NVIDIA, our employees are passionate about parallel and visual computing. We are united in our quest to transform the way graphics are used to solve some of the most complex problems in computer science. The GPU started out as an engine for simulating human imagination, conjuring up the amazing virtual worlds of video games and Hollywood films. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. NVIDIA is increasingly known as β€œthe AI computing company.” What you’ll be doing: As a key member of our ASIC Verification team, you will contribute to verifying graphics and compute features within an IP. You will be responsible for IP-level verification of GPU ASICs, including the design, architecture, golden models, and micro-architecture, using advanced verification tools and methodologies. You will work with the specifications, develop test plans, tests and verification infrastructure using UVM methodology and ensure functional and code coverage of all the RTL which you will verify. Work with HW architects and designers to make the right implementation choices. You will be working with architects, designers, and other members of yo

pythonartificial intelligenceai
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1mo ago

NVIDIA is leading the way in 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 amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. We are looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect -- for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models. Improve AI compilers to hide communications or perform automatic fusion. Conduct in-depth AI workload performance characterization on multi-GPU clusters. Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads. Author

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