8 Gpu Programming Jobs

Python, Deep Learning, Object Detection, Classification, Segmentation., GPU acceleration (CUDA, cuDNN). Model Optimization (pruning, quantization), deploying models to edge devices. Required Candidate profile willingness to explore and contribute to Generative AI and cloud-based AI solutions, C/C++., AWS Cloud AI/ML tools, exposure to GenAI frameworks like OpenAI, Stable Diffusion

raja.a@honeybeetechsolutions.com resume to FTE CLIENT PROXELERA / SASKEN 1. Strong hands-on experience in Linux (preferably Ubuntu or embedded Linux) 2. Experience in benchmarking CPU and GPU performance 3. Exposure to Android (performance optimization, debugging, or system-level work) 4. Experience working on x86 or ARM SoCs (e.g., AMD, Intel, Qualcomm, NVIDIA) 5. Demonstrated execution mindset individuals who are curious, quick learners, self-driven, and bring strong ownership and focus 6. 8+ years of relevant industry experience 7. Immediate availability or ability to onboard at short notice

Strong programming experience in Python, Solid background in deep learning, CNNs, and transfer learning and Machine learning basics, object detection, classification, segmentation, PyTorch, TensorFlow, and ONNX, GPU acceleration (CUDA, cuDNN).

Embedded platform development (Linux based distributions) & maintenance Linux build system expertise, packaging (RPM specification), build automation tool System Software (File system, Memory Management, Thread programming, Process Management, Platform Driver development/Integration, IPC, logging) Understanding about Compiler, toolchain development Different CPU Scheduling concept (SMP, HMP, FIFO, RT) System Level IPC expertise (User space, applications, middleware, kernel), logging framework System Level+B9 policies (memory, scheduler, CPU, hotplug) Platform porting & Reference Platform development on multiple chip-set Defect root-cause analysis & debugging utils (A9:G9gdb, objdump, Backtrace/Coredump analysis etc.) Performance/resource benchmarking & optimization (system boot-up/application launching/memory utilization etc.) - System Level Profiling, Tracing Full Software stack verification & Release management Platform Certification & Compliance Understanding

Blubridge is an LLM research lab focused on building next-generation Large Language Models and foundational AI systems. Alongside our research, we operate in the AI Consulting domain, delivering innovative AI solutions. We are rapidly scaling our GPU infrastructure and seeking a skilled Hardware/Systems Engineer to lead our compute backbone. Key Responsibilities: Architect, configure, and maintain high-performance GPU systems (H100, H200, B200, etc.) Design compute nodes and interconnects using PCIe, SXM, NVLink, InfiniBand Manage data center setups: rack layout, cooling, power, UPS/load balancing Build and maintain storage solutions (NVMe RAID, NAS/SAN) for AI workloads Benchmark and optimize hardware utilization (throughput, latency, bottlenecks) Collaborate with AI researchers to scale and troubleshoot workloads Manage Linux servers (Ubuntu, CentOS), BIOS tuning, firmware upgrades Monitor and automate compute cluster uptime and maintenance Required Qualifications & Skills: B.E/B.Tech in ECE, CSE, IT, Mechatronics, Robotics or related fields (2024/2025 pass-outs) Experience or projects in hardware system design, HPC setup, AI infrastructure Understanding of GPU architectures (PCIe vs. SXM, NVLink, GPU clustering) Familiarity with AMD EPYC/Intel Xeon, NVMe storage, 25G+ networking Knowledge of rack integration, thermal management, power planning Proficient in Linux server deployment and hardware automation Preferred: Experience with cloud/hybrid GPU infrastructure (AWS, OCI) Contributions to open hardware or benchmarking communities What We Offer: Ownership of AI labs hardware backbone Access to latest GPUs and enterprise-grade infrastructure Collaborative R&D environment Competitive salary and performance incentives Opportunity to impact AI infrastructure and consulting projects Apply now to join an innovative AI research and consulting team driving next-gen foundational models!

Minimum Qualifications: Experienced candidates (1 - 4 years) are welcome to apply with experience in the following area: Strong academic records (GPA 3.0 or 72% and better) Excellent programming skills in C/C++, Python Strong problem-solving skills Strong motivation and capabilities in learning new subjects especially in the field of artificial intelligence Knowledge of data-driven modelling Knowledge of computer and hardware architecture Effective interpersonal communications skill (written and verbal) Analytical, thorough, resourceful, and detail-oriented Self-motivated, hardworking, and flexible Preferred Qualifications: Basic understanding of machine learning, computer vision, and digital image processing algorithms and applications Advanced understanding of computer architecture Advanced understanding of data-driven modelling Excellent verbal, written, and presentation skills Ability to work effectively as part of a team Knowledge of OOP principles Knowledge of GPU Programming / Architecture is a bonus Minimum Education Required Masters/Bachelors Computer Engineering, Electrical Engineering or Engineering Science Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field.

Job Area: Engineering Group, Engineering Group > Systems Engineering General Summary: Do you ever wonder when will connected devices become thinking devices? Be part of the group that is working on technology that will bring "Cognition" to all connected devicesThat means devices that don"™t just think but instinctively react to their surroundings. We are searching for an AI Systems Architect Engineer to be part of the Qualcomm AI Processor team responsible for developing DSP and Machine Learning software applications and use cases developed for Qualcomm Snapdragon processors. The candidate will work on modelling and analysis of new cutting-edge algorithms in the areas of machine learning, computer vision and video processing that bring artificial intelligence to mobile and edge devices. Responsibilities include analyzing and optimizing custom processors/accelerators, developing and training data-driven architecture models, correlating these models, and performing system-level architecture analysis. Minimum Qualifications: Experienced candidates (1 - 4 years) are welcome to apply with experience in the following area: Strong academic records (GPA 3.0 or 72% and better) Excellent programming skills in C/C++, Python Strong problem-solving skills Strong motivation and capabilities in learning new subjects especially in the field of artificial intelligence Knowledge of data-driven modelling Knowledge of computer and hardware architecture Effective interpersonal communications skill (written and verbal) Analytical, thorough, resourceful, and detail-oriented Self-motivated, hardworking, and flexible Preferred Qualifications: Basic understanding of machine learning, computer vision, and digital image processing algorithms and applications Advanced understanding of computer architecture Advanced understanding of data-driven modelling Excellent verbal, written, and presentation skills Ability to work effectively as part of a team Knowledge of OOP principles Knowledge of GPU Programming / Architecture is a bonus Minimum Education Required : Masters/Bachelor"™s Computer Engineering, Electrical Engineering or Engineering Science Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field.

Develop and optimize HPC applications and algorithms using CUDA, MPI, OpenMP on Azure and cluster systems. Support scientific teams by modernizing codebases and enabling GPU acceleration. Required Candidate profile Software engineer with 5+ years in HPC programming, scientific code optimization, GPU computing, and collaboration with research teams.