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Performance Engineering Jobs in California (NOW HIRING)

Senior Performance Engineer

San Jose, CA ยท On-site

$138 - $206/hr

MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field. * B.S. with 5+ years of experience in performance engineering, AI systems, distributed systems, high ...

This role blends deep systems understanding with practical performance engineering--analyzing GPU kernel performance, collective communication throughput, investigating I/O bottlenecks, and sharding ...

Performance Engineer, GPU

San Francisco, CA ยท On-site

$280K - $850K/yr

Pioneering the next generation of AI requires breakthrough innovations in GPU performance and systems engineering. As a GPU Performance Engineer, you'll architect and implement the foundational ...

Training Performance Engineer

San Francisco, CA ยท On-site

$250K - $445K/yr

This role blends deep systems understanding with practical performance engineering - analyzing GPU kernel performance, collective communication throughput, investigating I/O bottlenecks, and sharding ...

Showing results 21-40

Performance Engineering information

See California salary details

$10

$59

$96

How much do performance engineering jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for performance engineering in California is $59.32, according to ZipRecruiter salary data. Most workers in this role earn between $48.65 and $67.12 per hour, depending on experience, location, and employer.

What is performance engineering?

Performance engineering is a discipline in software and systems development focused on ensuring applications and systems meet required speed, scalability, and stability standards. It involves analyzing, designing, testing, and optimizing performance throughout the software development lifecycle. Performance engineers use specialized tools and methodologies to detect bottlenecks, simulate real-world loads, and recommend improvements. Their goal is to deliver reliable, high-performing products to end users.

How does a performance engineer typically collaborate with development and operations teams to resolve application bottlenecks?

Performance Engineers play a vital role in bridging the gap between development and operations teams. They work closely with developers to analyze application code and identify potential performance issues early in the development lifecycle. Additionally, they partner with operations teams to monitor system performance in production, interpret logs, and recommend infrastructure or configuration changes. This collaborative approach helps ensure that performance bottlenecks are identified and addressed quickly, leading to more reliable and scalable applications.

What are the key skills and qualifications needed to thrive as a performance engineer, and why are they important?

To thrive as a Performance Engineer, you need strong analytical abilities, expertise in software performance testing, and a background in computer science or a related field. Familiarity with tools like JMeter, LoadRunner, APM solutions, and scripting languages is typically required, along with relevant certifications such as ISTQB Performance Testing. Exceptional problem-solving skills, attention to detail, and effective communication help you identify bottlenecks and collaborate with development teams. These skills are crucial for ensuring applications meet performance standards and deliver a seamless user experience.

What is the difference between Performance Engineering vs Performance Testing?

AspectPerformance EngineeringPerformance Testing
FocusDesigning, developing, and implementing strategies to ensure system performance throughout the development lifecycleExecuting tests to measure system performance under specific conditions
ActivitiesPerformance planning, monitoring, optimization, and capacity planningLoad testing, stress testing, and benchmarking
Skills & CertificationsPerformance testing tools, scripting, monitoring, performance analysisPerformance testing tools, scripting, test execution
Work EnvironmentCollaborates with developers, architects, and operations teamsPrimarily testing teams and QA departments

Performance Engineering involves proactive strategies to optimize system performance throughout development, while Performance Testing focuses on evaluating system performance through specific tests. Both roles require similar skills but differ in scope and objectives, with Performance Engineering being more comprehensive and ongoing.

How much do performance engineers make in the US?

Performance engineers in the US typically earn between $80,000 and $130,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in tools like JMeter or LoadRunner can command higher salaries, especially in tech hubs.

What do you need to be a performance engineer?

Performance engineers need a strong understanding of software architecture, performance testing tools, and scripting languages like Python or Java. They often have a background in computer science or engineering, experience with performance testing tools such as JMeter or LoadRunner, and knowledge of system monitoring and analysis. Certifications in performance testing or related fields can also be beneficial.

What are the most commonly searched types of Performance Engineering jobs in California?

The most popular types of Performance Engineering jobs in California are:

What cities in California are hiring for Performance Engineering jobs?

Cities in California with the most Performance Engineering job openings:

Infographic showing various Performance Engineering job openings in California as of August 2026, with employment types broken down into 82% Full Time, 14% Part Time, and 4% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $123,381 per year, or $59.3 per hour.

Senior Performance Engineer

Conductor

San Jose, CA โ€ข On-site

$138 - $206/hr

Other

PTO

Posted 5 days ago


Job description

Overview

Our technology solutions power the tools you use every day--including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more. Here, youโ€™ll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of whatโ€™s possible and powering the future.

We believe innovation and growth are driven by an inclusive culture and a diverse workforce. Weโ€™re dedicated to empowering people to be their true selves. Together, weโ€™re building a better tomorrow for our employees, customers, partners, and communities.

The AGI (Artificial General Intelligence) Computing Lab is dedicated to solving complex system-level challenges posed by future AI/ML workloads. Our team develops scalable platforms that handle computational and memory requirements while minimizing energy consumption and maximizing performance, collaborating closely with hardware and software engineers to address AI/ML workloads and explore new computing abstractions.

We are seeking a Senior LLM Systems Performance Engineer to build representative AI environments, characterize emerging workloads, and drive performance analysis for nextโ€‘generation AI platforms.

Location

Daily onsite presence at our San Jose, CA office / U.S. headquarters in alignment with our Flexible Work policy.

What Youโ€™ll Do
  • Build and operate representative AI environments, including agentic workflows, distributed inference systems, disaggregated serving architectures, and MoE deployments.
  • Collect workload traces, telemetry, and performance data from real-world AI applications; characterize workload behavior, develop representative benchmarks, and identify performance bottlenecks across compute, memory, communication, and scheduling resources.
  • Evaluate AI systems across the full hardware and software stack, and analyze the impact of runtime, memory hierarchy, interconnect, and accelerator architecture on application performance.
  • Collaborate with hardware and software teams to drive performance analysis, architecture exploration, and hardwareโ€“software co-design for nextโ€‘generation AI platforms.
What You Bring
  • MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
  • B.S. with 5+ years of experience in performance engineering, AI systems, distributed systems, high-performance computing, or a related area. MS in Computer/Electrical Engineering or Computer Science with 3+ years of relevant working experience or PhD and 0+ years of relevant experience preferred.
  • Strong understanding of LLM inference and training systems.
  • Strong understanding of NVIDIA GPU architecture and performance characteristics, including compute, memory hierarchy, communication, and systemโ€‘level bottlenecks.
  • Handsโ€‘on experience profiling and optimizing AI workloads on NVIDIA GPU platforms using tools such as Nsight Systems, Nsight Compute, and related performance analysis frameworks.
  • Experience analyzing performance of largeโ€‘scale distributed AI workloads.
  • Proficiency in Python and C++.
  • Experience with one or more modern AI frameworks or serving systems, such as PyTorch, vLLM, SGLang, TensorRTโ€‘LLM, DeepSpeed, Ray, or Megatronโ€‘LM.
  • Strong analytical and problemโ€‘solving skills.
Benefits
  • Competitive pay range: $138,000 - $206,000 USD.
  • Paid time off: 4+ weeks of PTO each year, plus holidays and sick leave.
  • Family support: stipend for fertility care or adoption, medical travel support, and virtual vet care for pets.
  • Wellโ€‘being: onโ€‘demand mental health apps, free confidential therapy sessions.
  • Fitness: onsite cafรฉ and gym, virtual classes.
  • Flexibility: benefits designed to fit individual needs.
Equal Opportunity Employment Policy

Samsung Semiconductor takes pride in being an equal opportunity workplace dedicated to fostering an environment where all individuals feel valued and empowered to excel, regardless of race, religion, color, age, disability, sex, gender identity, sexual orientation, ancestry, genetic information, marital status, national origin, political affiliation, or veteran status.

When selecting team members, we prioritize talent and qualities such as humility, kindness, and dedication. We extend comprehensive accommodations throughout our recruiting processes for candidates with disabilities, longโ€‘term conditions, neurodivergent individuals, or those requiring pregnancyโ€‘related support.

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