Top Tech Jobs & Startup Jobs in Pune

Develop automated software tests, validation tools, and AI-agentic workflows for NVIDIA Tegra-based Android, Linux, and proprietary platforms. Validate multimedia streaming, 4K HDR playback, cloud and local gaming, graphics, audio-video synchronization, latency, and stability. Analyze failures, triage defects, review requirements, improve coverage, report quality metrics, and collaborate with hardware, software, architecture, product, and release teams.

Develop system software and infrastructure for deploying, benchmarking, and qualifying local AI workloads across Linux and Windows GPU systems. Build CI pipelines, model management services, databases, data pipelines, dashboards, telemetry, scheduling systems, and autonomous infrastructure agents. Collaborate with inference and application teams to improve reproducibility, diagnose system issues, detect regressions, and optimize performance.

Develop AI-driven automated tests, Python tools, utilities, and frameworks for NVIDIA GPU drivers and SDKs across Linux systems. Analyze results, isolate defects, debug root causes, improve code coverage, validate compatibility across hardware and interfaces, and support CI/CD regression testing. The role also involves code reviews, technical reporting, task prioritization, and collaboration with engineering leadership. This is a fully onsite position.

Develops hardware-accelerated AI software for multimedia platforms, including audio, video, augmented reality, computer vision, and streaming applications. Responsibilities include designing algorithms, deploying applications across platforms, profiling and optimizing AI pipelines, addressing system-level resource challenges, and writing Python and C++ code. Requires substantial Linux software development experience, cloud-native architecture knowledge, and expertise in computer vision, machine learning, and deep learning.

Lead interaction design for NVIDIA gaming hardware, software, and services. Collaborate with researchers, engineers, product managers, visual designers, and cross-functional teams to create user-centered experiences. Develop journey maps, information architecture, prototypes, design specifications, visual and written assets, and design critiques. Use research data, metrics, business objectives, AI tools, and documentation tools to guide design direction.

Build and improve infrastructure supporting GPU firmware development, including build systems, regression farms, CI/CD pipelines, developer tools, test frameworks, web services, release pipelines, and observability. Debug issues across hardware, software, and processes; create AI-powered workflows; automate toil; and develop scalable internal tooling. Collaborate closely with hardware and software engineers while documenting requirements, designs, and trade-offs.

Develop and execute systematic software test plans for NVIDIA graphics, compute, and SOC products. Write tests, analyze results, document defects, troubleshoot test issues, maintain QA processes, and collaborate with development engineers to resolve problems. The role focuses on system software quality assurance rather than web testing, requiring PC and system assembly knowledge, hardware architecture understanding, and strong communication skills.

Supports SOX IT compliance by identifying risks, testing IT general and automated controls, documenting audit workpapers, evaluating deficiencies, and coordinating remediation. The role collaborates with process owners and external auditors, supports walkthroughs and testing, performs internal audit and AI automation projects, and maintains compliance documentation across SAP and third-party environments.

Lead the architecture and development of scalable full-stack Sales AI applications. Integrate generative AI models, retrieval systems, APIs, and agentic workflows into secure production solutions. Guide architecture across front-end, back-end, data, integrations, and cloud infrastructure while improving testing, delivery, observability, reliability, and maintainability. Lead technical decisions, investigate complex issues, mentor engineers, and collaborate with product, AI, data, security, and engineering teams.

Build and maintain system software and infrastructure for deploying, benchmarking, automating, and qualifying AI applications and models. Responsibilities include supporting inference backends, managing local model repositories, developing performance and correctness measurement systems, processing workload metrics, implementing diagnostics and observability, and maintaining automated build, integration, deployment, and qualification pipelines. The role also involves debugging system architectures, analyzing bottlenecks, and improving scalability across Linux and Windows environments.