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Senior System Software Engineer - Local AI Automation

Nvidia

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1,242 open automation roles across 286 companies are on ApplySarthi right now, most of them in Bengaluru (86), Hyderabad (31), Chennai (22).

What automation roles keep asking for: Python (32%), CI/CD (19%), SQL (18%), Agile (16%), AWS (16%), Test automation (12%), Azure (12%) — counted across their open postings here.

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Interviews for automation roles keep coming back to Python, CI/CD, SQL, Agile. Practise those questions before you sit with Nvidia.

Questions you are likely to be asked

  1. Why do you want to join Nvidia?
  2. What is your experience with Observability? Tell me one thing you learned the hard way.
  3. How did you know your model was actually good, and not just good on your test set?
  4. Tell me about a time the data was messy or wrong. What did you do?
  5. How would you explain your model's result to someone who is not technical?

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The Local AI Automation team is seeking a Senior System Software Engineer passionate about building and maintaining robust system-level software and infrastructure for deploying, benchmarking, and qualifying high-quality AI applications and models. You will collaborate with a team of highly qualified engineers dedicated to creating top-tier infrastructure for Local AI automation. If you have a real passion for building reliable, scalable automation systems in the AI ecosystem, this could be an excellent opportunity for us to work together! What you'll be doing: Design, implement, and maintain robust system software and infrastructure to efficiently run various AI workloads through different inference backends such as Llama.cpp, Ollama, PyTorch, vLLM, WinML, TRT-RTX, and others. Scope out system requirements for deploying various AI applications, benchmarks, and models in automation, and develop solutions to measure correctness, functionality, reliability, and overall system performance. Develop infrastructure to download AI models from various sources, efficiently manage a local model repository, and create automated synchronization mechanisms to keep the repository up to date. Analyze large datasets and system workload metrics, implement data processing infrastructure to transform raw data into actionable information for developers, and design useful visualizations. Collaborate with internal Local AI developers to identify and implement system-level instrumentation, diagnostics, and debugging capabilities that help quickly debug and isolate issues. Design, implement, and maintain robust infrastructure for automated build, integration, deployment, and qualification across different inference frameworks and environments. Understand existing infrastructure and system software architecture, debug issues in current frameworks, identify performance bottlenecks, and devise solutions to enhance system efficiency and scalability. What we need to see: 5+ years of experience with a B.Tech or higher degree in Computer Science, Information Technology, Software Engineering, or a related field. Strong analytical, systems debugging, and problem-solving abilities, with the capacity to multitask effectively in a dynamic environment. 5+ years of software development experience with strong programming skills in C/C++, C#, Java, or another systems programming language, along with exposure to at least one scripting language such as Python. Experience with system APIs, multithreaded software, process and resource management, debugging, or performance analysis. Familiarity with databases and SQL, source control systems, and CI/CD infrastructure such as Git, Perforce, and Jenkins. Outstanding written and oral communication skills, enabling effective collaboration with management and engineering teams. Ways to stand out from the crowd: Experience building robust system software, runtime infrastructure, or scalable backend components. Experience with system profiling, performance optimization, debugging, and telemetry/observability infrastructure, including analysis of Nsight Systems traces to understand system state and kernel performance. Hands-on background with Linux/Windows system programming, Git CI/CD, databases/SQL, Kubernetes, Docker, and observability tools such as Grafana or Kibana. Hands-on experience integrating or debugging inference frameworks such as Llama.cpp, Ollama, PyTorch, vLLM, WinML, or TRT-RTX. Experience understanding CPU/GPU resource utilization, memory management, concurrency, and performance characteristics of AI workloads. We are an equal-opportunity employer and value diversity at our company. With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.

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Listed on workday · posted 2026-10-12. ApplySarthi collects openings and links to application pages; the role is advertised by Nvidia, not by us.