At NVIDIA, our NVLink firmware powers the high-speed interconnect fabric at the heart of the largest multi-GPU systems globally — the backbone of modern AI and high-performance computing. Our Bangalore firmware development and validation team is responsible for this firmware end to end. They handle everything from feature creation to pre-silicon testing, silicon bring-up, and automation that keeps progress fast. This is firmware engineered at the edge of what the hardware allows — within tight boot-time and memory-footprint budgets where every byte counts. We are looking for a top-tier firmware engineer who is motivated by the full craft — writing the firmware, proving it accurate, crafting the tooling and infrastructure strategy that makes the whole team faster, and setting the technical bar for everyone around them. The work spans next-generation GPU platforms and puts you shoulder to shoulder with architecture, hardware, and build teams across our Bangalore and American locations. If you love low-level software, thrive on debugging the hardest problems, and want your work to ship in the systems that define the industry, we’d love to meet you.
What you’ll be doing:
Own the technical architecture and roadmap for NVLink and high-performance interconnect firmware across next-generation GPU platforms — staying hands-on in C, C++, and Python on the highest-leverage problems.
Take end-to-end ownership of sophisticated interconnect features, driving seamless execution from design through final verification.
Architect correctness models, verification plans, and test cases — primarily in Python — to prove firmware functionality across both pre-silicon and post-silicon environments.
Shape silicon bring-up, design-for-debug, and program-level validation strategy with architecture, hardware, and design leads across Bangalore and US sites.
Define the verification methodology, engineering standards, and quality gates the team builds to — and the automation strategy that scales them.
Advance the team’s AI-assisted, agentic debug and root-cause tooling, raising how fast the team resolves the hardest failures.
Grow the team’s technical capability — mentoring engineers, raising the quality bar, and de-risking the hardest cross-generation problems before they land.
What we need to see:
BS or MS degree (or equivalent experience) in Electrical Engineering, Computer Science, or a related field.
10+ years of experience in firmware or software development and verification.
Deep programming proficiency in Python, C, and C++, with strong command of object-oriented design.
Strong understanding of computer architecture, microprocessors, and microcontroller fundamentals.
Expert debugging and analytical skills that span the hardware/software boundary.
A track record of technical leadership — setting direction, mentoring engineers, and raising quality across a team.
Excellent collaboration and communication skills, with proven success in a multi-national, multi-time-zone environment spanning on-site and remote teams.
A highly motivated, creative problem-solver with a passion for deep-tech and a bias toward rigorous testing.
A versatile, self-motivated approach — equally at home in development, verification, and infrastructure.
Ways to stand out from the crowd:
Depth in test automation and test-case design — building maintainable frameworks that cover edge cases and critical scenarios.
Familiarity with secure development techniques: threat modeling, static and dynamic code analysis, fuzzing, and negative testing.
Experience with multi-core, multi-process, and multi-threaded programming.
Exposure to high-performance computing systems, interconnects, or networking protocols and architectures.
Passion for unlocking the potential of yourself and those around you.
Skills Required
- BS or MS degree (or equivalent experience) in Electrical Engineering, Computer Science, or related field.
- 10+ years of experience in firmware or software development and verification.
- Deep programming proficiency in Python, C, and C++ with strong object-oriented design.
- Strong understanding of computer architecture, microprocessors, and microcontroller fundamentals.
- Expert debugging and analytical skills spanning the hardware/software boundary.
- Track record of technical leadership, mentoring engineers, and raising team quality.
- Excellent collaboration and communication skills in multinational, multi-time-zone environments.
- Highly motivated, creative problem-solver with a bias toward rigorous testing.
- Versatile, self-motivated approach across development, verification, and infrastructure.
- Depth in test automation and test-case design (Ways to stand out).
- Familiarity with secure development techniques: threat modeling, static/dynamic analysis, fuzzing (Ways to stand out).
- Experience with multi-core, multi-process, and multi-threaded programming (Ways to stand out).
- Exposure to high-performance computing systems, interconnects, or networking protocols and architectures (Ways to stand out).
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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