158 Gpu Jobs - Page 7

Software Architect Generative AI & LLM Systems job location Hyderabad - Noida or Gurgaon Job Overview We are seeking a highly experienced and hands-on Software Architect to lead the design and deployment of Large Language Model (LLM)-powered applications across cloud and on-prem environments. This role demands deep expertise in full-stack software development, high-performance inference systems, and cutting-edge generative AI workflows. You will play a key role in scaling AI infrastructure, maximizing throughput, and educating cross-functional teams on best practices for building LLM-driven solutions. Key Responsibilities LLM Deployment & Infrastructure Design: Architect, deploy, and maintai...

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.

Job Title : C++ Developer Duration : 1-year contractual position Experience Range : 4 to 6 years Notice Period : Within 20 days Location : Kandivali, Mumbai (Only local candidates of Mumbai are acceptable) Education : B.Tech, B.E Interview Process : 1st- Technical, 2nd - Technical round & 3rd - HR Round Mandatory : End-to-end C++ skills Job Description : We are seeking an experienced Developer with a strong background in C++, CUDA programming, and Linux to guide our development team in building cutting-edge solutions for device integration and high-performance computing tasks. This is a hands-on leadership position that combines technical expertise with team management skills to deliver high...

Role & responsibilities ML Engineer 4-5yrs or above experience. They mentioned, yes, please explore. They want ML Engineering, Backend developers with ML deployment. Few of the skills that he mentioned, Grafana, Karpenter, Keda, Python, Golang. GPU understanding.

Designing and implementing groundbreaking GPU computers that run demanding deep learning, high-performance computing, and computationally intensive workloads Optimise Computer Vision Algorithms, Hardware Accelerators for performance & quality KPIs Required Candidate profile Optimize algorithms for optimal performance on the GPU tensor cores Strong Data structures and Algorithms know-how Hand-on expertise with GPU computing (CUDA, OpenCL, OpenACC) and HPC (MPI, OpenMP)

Position : Machine Learning Engineer - Generative AI / LLMs (Onsite - Bengaluru) Experience : 3+ years of industry experience in ML, software engineering, and data engineering. Education : Masters degree or equivalent experience in Machine Learning. Location : Bangalore (HSR Layout) Job Description: We are looking for a talented Machine Learning Engineer to join our AI team at our Bengaluru office (Onsite Only). In this role, you will work on cutting-edge solutions leveraging Generative AI, Large Language Models (LLMs), NLP, and Computer Vision to solve complex real-world problems. Responsibilities: Design, build, and deploy ML models for NLP, Computer Vision, LLMs, and Generative AI use cas...

Job Title : C++ Developer Duration : 1-year contractual position Experience Range : 4 to 6 years Notice Period : Within 20 days Location : Kandivali, Mumbai (Only local candidates of Mumbai are acceptable) Education : B.Tech, B.E Interview Process : 1st- Technical, 2nd - Technical round & 3rd - HR Round Mandatory : End-to-end C++ skills Job Description : We are seeking an experienced Developer with a strong background in C++, CUDA programming, and Linux to guide our development team in building cutting-edge solutions for device integration and high-performance computing tasks. This is a hands-on leadership position that combines technical expertise with team management skills to deliver high...

Years of experience required: 8-12 with min 5+ in suitable area 4. GCC/non-GCC status: Non GCC 5. Location: Bangalore Perform system-level validation and debug of heterogeneous HPC compute subsystems involving CPU clusters, GPUs, AI accelerators, memory interconnects, and HSIO interfaces. Workload-oriented validation to ensure scaling, performance, and reliability. Validate CPU/GPU pipelines, AI engines, and shared memory interactions in server SoCs. Run performance and stress workloads (MLPerf, GPGPU, HPC apps) across compute domains. Debug coherency, cache, memory access, and interconnect issues (PCIe, CXL, HBM/DDR). Validate system-level power states, boot flows, and driver stack interact...