Level

NVIDIA

Senior System Software Engineer - Local AI

NVIDIA is hiring a Senior System Software Engineer - Local AI in Pune, India. Level rates it ; you can apply on Level.

Level's read on this job

  • Builds AI ●●●● is how Level rates this software engineer role: the job is building AI systems.
  • Tools and skills the posting cites include Llama, Ollama and vLLM.
  • Level files it as a senior role.
  • Level lists 2,700+ other open roles at NVIDIA.
  • The role was posted in the last few days.

AI in this role

llamaollamavllmpytorch
ai-agentsai-evaluation

NVIDIA has continuously reinvented itself for over two decades. The invention of the GPU in 1999 fueled the growth of PC gaming, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning has ignited modern AI, positioning NVIDIA as a leading AI computing company.


Artificial intelligence is shifting from passive assistance to autonomous, always-on workflows. Our mission is to make this transition seamless, efficient, and secure for millions globally. The Local AI Inference team is seeking a Senior System Software Engineer to lead the development of robust system-level software and infrastructure for deploying, benchmarking, and qualifying high-quality AI applications and models across Linux and Windows systems powered by RTX and DGX-class GPUs. You will partner with inference engineers, model developers, and AI application teams to build reliable, scalable infrastructure that enables reproducible evaluation and improves local AI performance. Using AI tools and developing autonomous agents, you will accelerate infrastructure development, automate operations, and help engineers diagnose complex system issues. If you enjoy tackling systems challenges and shaping how AI infrastructure is built and operated, we would love to hear from you!


What you'll be doing:

  • Partner across organizations with benchmarking teams, inference teams, and AI application developers to define requirements, design, and maintain shared infrastructure for deploying, benchmarking, and qualifying AI workloads across infernece backends such as llama.cpp, Ollama, PyTorch, vLLM, and WinML.
  • Build Git-based CI infrastructure for automated builds, integration testing, and regression detection across hardware platforms, operating systems, and runtime configurations.
  • Develop model management services to download, version, cache, and synchronize checkpoints and dependencies for reproducible execution.
  • Design databases, backend services, and data pipelines to store and query model metadata, benchmark results, system telemetry, and execution artifacts.
  • Create dashboards and reports that help engineers compare inference configurations, identify regressions, and investigate performance bottlenecks.
  • Develop and operate server infrastructure, including environment provisioning, workload scheduling, resource management, and failure recovery.
  • Develop autonomous AI agents for infrastructure management, workload orchestration, monitoring, and diagnostics, with appropriate access controls and execution safeguards.
  • Maintain Git repositories and companion websites, keeping code, documentation, model recommendations, and evaluation results current.
  • Collaborate with inference developers to implement instrumentation and debugging capabilities, resolve system issues, and improve infrastructure efficiency and scalability.

What we need to see:

  • B.Tech or higher degree in Computer Science, Computer Engineering, Information Technology, Software Engineering, or a related field, or equivalent experience.
  • 5+ years of relevant software development, with strong programming skills in Python, C/C++, C#, or another systems programming language.
  • Experience developing system software, backend services, or infrastructure supporting engineering development.
  • Understanding of system APIs, multithreading, process and resource management, and systems debugging.
  • Hands-on with Git-based CI, databases, SQL, and data modeling.
  • Strong analytical and problem-solving skills, with the ability to independently own projects and manage competing priorities.
  • Excellent written and verbal communication skills for collaboration across engineering teams.

Ways to stand out from the crowd:

  • Track record of integrating or debugging AI inference frameworks and building model evaluation or benchmarking platforms
  • Proficiency working with AI agents, including tool integration and evaluation of autonomous infrastructure workflows.
  • Hands-on expertise in developing telemetry and observability systems using tools such as Grafana or Kibana.
  • Demonstrated ability to publish technical documentation, model recommendations, or benchmark results through companion websites.

We're a top employer known for innovation and growth. 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 world’s most desirable employers of technology. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we would like to hear from you. 

How we rate this

Senior System Software Engineer - Local AI at NVIDIA rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsAI EvaluationLlamaOllamavLLMPyTorch

Also common in software engineer jobs at this level

Pay

Typical software engineer job
$168k

This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. How do you decide that one model's output is better than another's for a given task?
  3. What are the limits of Llama that you've run into, and how did you work around them?
  4. What's a project where you used Ollama hands-on?
  5. Walk me through how you've used vLLM in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: AI agents, AI Evaluation, Llama, Ollama, and vLLM. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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