4 Gpgpu Jobs

You should have a Ph.D. in relevant domains with expertise in Biometric Recognition technologies such as Fingerprint, Iris, and Vein, as well as experience in Augmented Reality (AR) and Virtual Reality (VR). Your background should include knowledge in Multi-view, Stereo, and Depth technologies. Ideally, you hold a degree in EE/Electrical Engineering, with either a BS or MS from a top US school. Your skill set should encompass expertise in Algorithms, Sensor technologies including array sensors, multi sensors, and 2PD sensors. Experience in Vision and Imaging, Computational Photography, and computer vision is essential. You should be well-versed in Image and Video Pipeline, Multimedia Frameworks, and Security protocols. Knowledge in Heterogeneous Computing, Graphical Processor Unit (GPU) design, and software frameworks like Open CV, OpenVX, OpenGL, and GPGPU is required. Familiarity with Codec design, particularly H.264/V8 designs, as well as 3D technologies, Hardware accelerators, and RTL design is beneficial. Experience in Display controllers, Display processing, Low Light video and image capture, and IPI CSI/MIPI-DSI working and design is a plus. If you possess the above qualifications, kindly get in touch with Ram at Mobile: +91 98 1845 4080 / 98 6860 9864 for further discussions. Please note: This job description was sourced from hirist.tech.,

Job Title: C++ Developer Contractual | Immediate Joiner | Mumbai (Onsite) Job Description: We are hiring for a C++ Developer position for one of our esteemed clients, a leader in device integration and high-performance computing. This is a 1-year contract-based opportunity with the potential for extension or permanent absorption based on performance. The role is onsite at Kandivali, Mumbai, and is open strictly to local candidates who are available to join within 20 days. The ideal candidate will be a passionate and experienced developer with end-to-end C++ development expertise, along with proficiency in CUDA programming, GPU performance tuning, and parallel computing. You will be working on real-time, high-performance applications and GPU-accelerated tasks, collaborating closely with software engineers and researchers to bring innovative solutions to life. Key Responsibilities: Develop and maintain high-performance software applications using modern C++ (C++11/14/17/20). Design and implement GPU-accelerated algorithms using CUDA to optimize system performance. Optimize CUDA kernels for memory efficiency, scalability, and overall performance. Conduct code reviews to ensure adherence to best practices and clean coding standards. Create and execute test plans to validate performance and functionality. Analyze and troubleshoot performance bottlenecks using appropriate debugging and profiling tools. Collaborate with cross-functional teams including product development, QA, and R&D to deliver robust and reliable software. Provide technical mentorship to junior developers as needed. Maintain clear and comprehensive documentation for all software components and processes. Required Skills & Experience: 4 to 5 years of hands-on experience in C++ software development. Strong command of modern C++ standards (C++11/14/17/20). Proven experience with CUDA programming and developing GPU-accelerated solutions. Good understanding of parallel computing, multithreading, and GPU architecture. Experience with CUDA optimization techniques: memory hierarchy, streams, warp-level primitives, etc. Familiarity with tools such as Nsight, CUDA Memcheck, or other debugging/profiling utilities. Strong analytical and mathematical skills including knowledge of linear algebra and numerical methods. Job Details: Location: Kandivali, Mumbai (Only local candidates will be considered) Work Mode: Work From Office (No hybrid/remote options) Type: Full-time, Contractual 1 Year Notice Period: Immediate joiners or max 20 days Why Apply Opportunity to work on cutting-edge CUDA and high-performance computing projects. Exposure to a highly technical and collaborative environment. Chance for contract-to-hire based on performance. Note: This role is strictly for candidates who are currently based in Mumbai and can join on short notice. Profiles from other locations will not be considered. Key Skills: C++, CUDA, GPU Programming, Parallel Computing, Multithreading, Nsight, Memory Optimization, High-Performance Computing, CUDA Kernel Development

The candidate will be responsible for implementing computer vision algorithms on target platforms, optimizing the code for the platform's resources, and managing end-to-end workflow efficiently. The ideal candidate should have a minimum of 3 years of relevant experience and possess knowledge of Processing elements such as Multicore CPU with one or more of DSP, GPGPU, FPGA. Experience in video protocols, input/output video (Ethernet streaming video, USB, MIPI CSI), Serial (RS422/232), GPIO, Ethernet, USB, and video processing on target hardware is highly desirable. If you are a fresh graduate or post-graduate engineer with a passion for technology and a keen interest in cutting-edge research work, Inferigence Quotient LLP welcomes you to join our team. If you are eager to learn and contribute effectively, please send your application to hr@inferq.com.,

Strong fundamentals in C/C++ and OS internals Strong knowledge of and experience with LLVM, tvm especially middle-end compilers. Knowledge and experience with graphics/compute APIs such as OpenCL, cuda, Vulkan, OpenGL or DirectX An appreciation of multi-threaded and/or parallel computation and associated complexity Knowledge of GPGPU programming Knowledge of AI/ML workloads that are amenable to GPU execution This is what you are responsible for Design and develop the application and system software for a cutting-edge AI silicon Ability to work in a fast-paced environment collaborating with various teams locally and globally A passion for problem-solving and the ability to consider the bigger picture during feature development Define feature requirements with customers and teams, gathering feedback to improve products Ensure clear understanding of requirements, documenting implementation strategies Review and test features to prevent issues, conducting impact analysis to mitigate potential problems