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Full-time
bachelor degree, postgraduate degree
Posted 16d ago
~40 hrs/week
Responsibilities
Design and develop high-performance, low-latency video streaming functionalities to improve image quality and system reliability. Analyze GPU/CPU performance bottlenecks and integrate AI models to optimize adaptive streaming algorithms.
Requirements
Requires 5+ years of experience with a degree in Computer Science and proficiency in C, C++, and Python. Must have deep knowledge of real-time video codecs, GPU API frameworks, and objective video quality assessment metrics.
Full job description
NVIDIA's GeForce NOW, the next-generation gaming service powered by NVIDIA GPUs in the cloud, transforms a Mac, PC, or mobile device into a high-performance gaming machine. GeForce NOW keeps games up-to-date automatically, enabling users worldwide to instantly stream the latest games in high-definition resolution with minimal latency and the smoothest gameplay. Just click and play! Visit us at https://www.nvidia.com/en-us/geforce-now. We are now extending this industry defining technology to a new range of applications including virtual and augmented reality, artificial intelligence and remote controlled robotics.
We are seeking a Senior Software Engineer to join a team of skilled and motivated engineers who develop a high performance, low latency streaming stack that delivers unprecedented video quality at lowest latency that makes gaming from the cloud the preferred gaming platform for millions.
What you will be doing:
Design and develop new video streaming functionalities delivering new interactive experiences
Innovate, design and develop features to improve image quality, performance, reliability, security and maintainability
Analyze GPU/ CPU performance for the video pipeline, isolate bottlenecks and implement solutions in collaboration with GPU hardware and software teams to deliver top performance
Develop tools to measure video quality experienced by users, refine to enable evaluation of quality improvements with high confidence
Leverage features and toolsets in latest video compression technologies to deliver high quality streaming solutions tailored for different interactive graphics applications
Develop quality-evaluation and analysis capabilities that use metrics along with encoder statistics to detect regressions, evaluate new video features, and guide codec and pipeline tuning.
Apply machine learning and AI models to develop specialized video processing and adaptive streaming algorithms to minimize perceptible artifacts while delivering the lowest latency under different network conditions.
What we need to see:
5+ years of experience with Bachelor's or Master's degree in Computer Science or a related area.
Proficiency in C, C++, Python
Strong understanding of real-time GPU-accelerated video pipeline performance, including encoder behavior, color spaces, video scaling, transport efficiency, buffering, pacing, bitrate adaptation, frame handling, and latency-sensitive optimizations in distributed or cloud-based systems.
Familiarity with API frameworks such as Vulkan, CUDA, OpenGL and DX
Solid understanding of toolsets in different video codecs like H.264, HEVC, and AV1, including tuning codec configurations to meet application requirements and trade-offs.
Experience debugging and improving reliability and stability in complex streaming systems, including issues related to degraded network conditions, packet loss recovery, telemetry, tracing, field validation, and long-running session behavior.
Proficiency in telemetry, statistical data analysis, and performance monitoring to measure and optimize video quality, latency, and system performance in cloud infrastructures.
Experience in using and integrating AI models into real-time video pipelines
Experience with objective video quality assessment using metrics such as VMAF, CAMBI, PSNR, and SSIM/MS-SSIM, and the ability to correlate those metrics with perceptual video quality across different content types and artifacts.
Strong understanding of different layers of software stack including OS internals, user-mode and kernel-mode drivers, strong system software performance analysis, testing and debugging skills
Ways to stand out from the crowd:
Experience in optimizing video pipelines on multiple GPU families such as Intel integrated and AMD GPUs
Experience writing or analyzing graphics rendering applications or advanced AI based graphics generation such as DLSS, RTX, FSR
At NVIDIA, we’re committed to diversity, equity, and inclusion. We embrace diverse perspectives and are proud to be an equal opportunity employer.
Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.
Offices: 2701 San Tomas Expressway, Santa Clara, CA 95050, US · No. 8, Ji Hu Rd., Taipei City, Taipei City 114, TW · Nanakramguda, Serilingampally Mandal, Plot # 6A&B, IT Park Layout, RR District, Hyderabad, Telangana 500046, IN · No. 127 Andheri Kurla Road, CNB Square, Mumbai, Village Chakala, Andheri East 400 093, IN · Survey No. 144/145, Samrat Ashok Path, Off Airport Road, Pune, Yerwada 411 006, IN
How many Software jobs are open in pune, India right now?
There are currently 4,514 open software positions in pune, India listed on Clera. New openings are added daily as companies post roles.
Which companies are hiring for Software roles in pune, India?
Companies currently hiring include Accenture, Barclays Corporate Banking, Capgemini, YASH Technologies, Mastercard, among others. Browse the listings above to see every active employer.
Are there remote or hybrid Software jobs in pune, India?
Yes — 744 of the 4514 open software positions offer remote or hybrid work (76 remote, 668 hybrid).
How do I apply for Software jobs in pune, India?
Each listing links directly to the employer's application page. Apply early — fresh listings get the most recruiter attention in the first two weeks.