Performance Engineer Jobs in Santa Clara, CA
Performance Engineer jobs in Santa Clara are concentrated in the Central Expressway corridor, the Santa Clara Square district, and the tech campuses along Tasman Drive, across semiconductors, cloud infrastructure, and enterprise software. Companies actively hiring include NVIDIA, Apple, and AMD. Find a role that fits below and apply directly.
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NVIDIA is redefining accelerated computing and powering the next era of artificial intelligence. Our data-center platforms bring together GPUs, CPUs, networking, systems, and software to solve some of the world’s most exciting computing problems. We are looking for a System Software Engineer to join NVIDIA’s GPU Performance and Power Management Software team. You will help design, develop, and debug production software for performance states (P-states) and Power Management Controllers. Your work will also support dynamic voltage and frequency scaling (DVFS) and power-management technologies for next-generation data-center GPUs.
You will work at the intersection of hardware architecture, embedded firmware, device drivers, operating systems, and AI workloads. In this role, you will contribute across the product lifecycle, including design, pre-silicon development, validation, silicon bring-up, and production support. This is a great opportunity to build expertise in GPU power and performance software while contributing to products that deliver leading performance, energy efficiency, and reliability.
What You’ll Be Doing:
- Design, build, implement, and debug GPU power- and performance-management software, with emphasis on P-state management and DVFS.
- Develop control policies and software mechanisms that optimize GPU performance, power, thermals, and energy efficiency under demanding data-center workloads.
- Support features through full product lifecycle: requirements, architecture, implementation, pre-silicon validation, silicon bring-up, productization, and production support.
- Collaborate with GPU architects and hardware designers to define and implement hardware-software interfaces for next-generation processors.
- Analyze interactions among workloads, clocks, voltages, power limits, thermals, telemetry, and system-level policies.
- Investigate, triage, and resolve power, performance, stability, and reliability issues spanning firmware, drivers, hardware, and platform software.
- Help execute validation strategies and automation for functional correctness, transition latency, performance-per-watt, and robustness across operating conditions.
- Write clear technical documentation, interface definitions, for features.
- Partner with distributed teams across architecture, ASIC, firmware, driver, validation, platform, and data-center systems.
What We Need to See:
- BS or MS degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent experience.
- 2+ years of relevant industry experience, or strong coursework, internship, co-op, or project experience in system software.
- Strong programming skills in C, with the ability to develop, debug, and maintain low-level kernel software.
- Good understanding of operating-system fundamentals, computer architecture, device-driver architecture, embedded or real-time software, concurrency, interrupt handling, and hardware programming
- Ability to independently debug and analyze across multiple layers of software and hardware.
- Ability to read and understand hardware specifications and software interface definitions.
- Strong problem-solving skills and willingness to learn from and work effectively with cross-functional teams.
- Excellent written and verbal communication skills.
Ways to Stand Out From the Crowd:
- Hands-on, Internship or project experience with GPU, CPU, accelerator, or SoC power and performance management.
- Coursework or project work in computer architecture, operating systems, control systems, or power/performance optimization.
- Exposure to P-states, DVFS, clock control, voltage control, thermal management, or workload-aware system behavior.
- Familiarity with validation, scripting or automation, and telemetry analysis for low-level software features. Strong understanding of hardware-software interactions.
- Experience with AI tools leverage for SW engineering work - coding, validation, automation workflows
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
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.See All 165+ Performance Engineer Jobs in Santa Clara
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Find Performance Engineer JobsPerformance Engineer Job Market in Santa Clara
Who's Hiring
- NVIDIA91

- Apple28

- AMD23

- Qualcomm17

Top Industries Hiring
- Technology & Software46
- Electronics & Hardware34
- Law & Legal Services17
- Telecommunications11
Performance Engineer Jobs in Santa Clara: Frequently Asked Questions
How do I get a performance engineer job in Santa Clara?
Focus your search on Santa Clara's semiconductor, cloud infrastructure, and enterprise software sectors, where performance engineering demand is consistently strongest. The campuses along Tasman Drive, Great America Parkway, and the Santa Clara Square area house a dense concentration of relevant employers. Candidates who can demonstrate proficiency with load testing, capacity planning, or hardware-level optimization stand out in this market, especially with experience on high-throughput or latency-sensitive systems common here.
Which companies hire performance engineers in Santa Clara?
Santa Clara performance engineer roles are posted by NVIDIA, Apple, and AMD and others right now, based on current listings on Migrate Mate as of October 2026. The city is home to a mix of global semiconductor firms, hyperscaler data center operators, and enterprise technology companies, all of which maintain ongoing performance engineering headcount.
Are there remote performance engineer jobs in Santa Clara?
Yes, though availability depends on the role: analytical and software-focused performance work is more remote-friendly, while hardware validation and on-site lab testing typically require physical presence. About 28% of performance engineer openings tied to Santa Clara are remote or hybrid as of October 2026, reflecting the mix of desk-based and lab-based work in the local market. Cloud and application performance roles in Santa Clara trend most remote.
How can I get a performance engineer job in Santa Clara with little or no experience?
The most realistic entry path in Santa Clara is landing a junior or associate QA, software engineer in test, or systems validation role at one of the city's many mid-size semiconductor or infrastructure companies, which tend to hire earlier-career candidates more actively than large enterprise firms. Internships and co-op programs at Santa Clara's tech campuses frequently convert to full-time offers. Building hands-on experience with profiling tools, benchmarking frameworks, or automation scripting gives candidates a concrete edge in local interviews.
Which industries hire the most performance engineers in Santa Clara?
Santa Clara performance engineer roles concentrate in Technology & Software, Electronics & Hardware, and Law & Legal Services, based on current listings on Migrate Mate as of October 2026. Santa Clara's position as a global hub for chip design, data center hardware, and cloud platform development creates sustained demand for engineers who can optimize system performance at both the silicon and software layers.
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