Senior System Software Engineer
Overview
- Added in 30 days
- 647
- At this company, still open
Skills named in this posting
- Python
- Boot firmware
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people.
Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
NVIDIA pioneers innovative tech in computer graphics, gaming, and AI, seeking Sr System SW Engineers in Pune, India.
What you'll be doing:
• Drive comprehensive power, performance, and Perf/Watt measurements on SoC and system platforms, with a strong emphasis on Windows on ARM (WoA) devices.
• Characterize system behavior across different states, idle, active, and low-power states, especifically optimizing Hours of Battery Life (HOBL) scenarios (e.g., Productivity, Web Browsing, Conferencing, Video Streaming, Modern Standby).
• Analyze power telemetry, firmware traces, and OS metrics to identify and mitigate bottlenecks, driving flawless performance.
• Design, build, and scale automated power measurement infrastructure, integrating Data Acquisition systems (DAQs), telemetry parsers, and ETL pipelines from the ground up.
• Collaborate closely with hardware architecture, BIOS/FW, OS, and driver teams to enable and tune new power features (DVFS, deep C-states, idle power gating) from Pre-Silicon modeling through Post-Silicon bring-up.
• Develop advanced visualization and detailed reports to summarize product health trends, isolate regressions, and recommend architectural or software optimizations to executive and engineering teams.
What we need to see:
• 5+ Years of experiene with Bachelor’s or Master’s degree or equivalent in Electrical Engineering, Computer Engineering or a related field.
• Strong grasp of foundational and advanced power management concepts: Low Power Modes, P-states, C-states, S0ix/Modern Standby, DVFS, package power limits, and thermal throttling.
• Proven experience with power tools on Windows/Linux platforms, such as WPA, HWInfo, ETL, Xperf, and PowerCfg.
• ISolid understanding of SoC architecture, including CPU, memory, I/O subsystems, and firmware (BIOS/UEFI/EC).
• Proficiency in scripting languages such as Python, PowerShell, or Bash for test automation and data parsing.
• Proven ability to analyze complex execution metrics (latency, throughput, utilization) and balance power vs. performance trade-offs.
Ways to stand out from the crowd :
• Direct experience debugging and optimizing multimedia or display hardware offload pipelines for power savings.
• Experience building scalable lab infrastructure, databases, or ETL pipelines for high-volume lab telemetry.
• Exposure to integrating AI/ML models for anomaly detection, regression tracking, or predictive power estimation.
• Hands-on experience with SoC validation tools, thermal chambers, and high-resolution power analyzers (NI, Yokogawa, Agilent/Keysight).
• Knowledge of battery modeling and energy efficiency benchmarking.
Join NVIDIA, where we strive for excellence and innovation in everything we do!
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
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Original posting: jobs.nvidia.com
RISC-V ecosystem
NVIDIA Corporation in the RISC-V ecosystem
RISC-V International: Premier Board
Founded in 1993, NVIDIA is an AI computing company. The company is headquartered in Santa Clara, California.
- NVIDIA is bringing CUDA platform support to RISC-V, i.e. allowing a RISC-V CPU to host CUDA GPU applications
- Publicly credited the RVA23 profile as the enabler: "We wouldn't have considered porting CUDA to RISC-V without it"
- Active in RISC-V International profile/standards work and a frequent presence in RISC-V ecosystem coverage
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