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Performance Engineering Jobs in California (NOW HIRING)

Anthropic

Performance Engineer, GPU

San Francisco, CA · 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 ...

OpenAI

Training Performance Engineer

San Francisco, CA · 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 ...

Slope

Training Performance Engineer

San Francisco, CA · On-site

$250 - $460/hr

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

OpenAI

Performance Modeling Engineer ~2

Los Angeles, CA · On-site

$266 - $445/hr

... engineering, systems analysis, or performance modeling who are excited to grow in large-scale infrastructure and hardware/software systems. This role is based in San Francisco, CA. We use a hybrid ...

Figure

Helix AI Engineer, Training Performance

San Jose, CA · On-site

$200K - $400K/yr

Bachelor's or Master's degree in Computer Science, Computer/Electrical Engineering, or a related field * 3+ years in AI performance engineering, with significant time leading large-scale performance ...

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Performance Engineering information

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How much do performance engineering jobs pay per hour?

As of Aug 16, 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 the job of a performance engineer?

A performance engineer is responsible for analyzing, testing, and optimizing software or systems to ensure they meet performance standards such as speed, scalability, and reliability. They use tools like load testing and monitoring software to identify bottlenecks and improve system efficiency, often working closely with development and operations teams.

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 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.

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.

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:

Performance Engineering jobs near you
Infographic showing various Performance Engineering job openings in California as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $123,381 per year, or $59.3 per hour.

Senior Performance Engineer

Samsung Semiconductor Inc.

San Jose, CA • On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 16 days ago

Samsung Electronics rating

6.7

Company rating: 6.7 out of 10

Based on 50 frontline employees who took The Breakroom Quiz

125th of 157 rated electronics manufacturers

Job description

Please Note:

To provide the best candidate experience amidst our high application volumes, each candidate is limited to 10 applications across all open jobs within a 6-month period.

Advancing the World's Technology Together

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

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

The AGI (Artificial General Intelligence) Computing Lab is dedicated to solving the complex system-level challenges posed by the growing demands of future AI/ML workloads. Our team is committed to designing and developing scalable platforms that can effectively handle the computational and memory requirements of these workloads while minimizing energy consumption and maximizing performance. To achieve this goal, we collaborate closely with both hardware and software engineers to identify and address the unique challenges posed by AI/ML workloads and to explore new computing abstractions that can provide a better balance between the hardware and software components of our systems. Additionally, we continuously conduct research and development in emerging technologies and trends across memory, computing, interconnect, and AI/ML, ensuring that our platforms are always equipped to handle the most demanding workloads of the future. By working together as a dedicated and passionate team, we aim to revolutionize the way AI/ML applications are deployed and executed, ultimately contributing to the advancement of AGI in an affordable and sustainable manner. Join us in our passion to shape the future of computing!

This role is offered by the STG group within the AGI Lab as part of DSRA. We are a systems research and engineering team working at the intersection of large language models, accelerator hardware, and high-performance software. Our mission is to design, prototype, and optimize next-generation AI systems through tight hardware-software co-design. Our team works hands-on with cutting-edge accelerator hardware, advanced memory systems, and large-scale distributed AI infrastructure. We develop and optimize the software stack required to maximize performance, efficiency, and scalability for modern and emerging LLM workloads.

We are seeking a Senior LLM Systems Performance Engineer to build representative AI environments, characterize emerging workloads, and drive performance analysis for next-generation AI platforms. In this role, you will set up and operate realistic LLM serving and agentic AI environments, collect workload traces and performance data, and develop methodologies to characterize workload behavior. You will analyze system bottlenecks across compute, memory, communication, and scheduling resources, and evaluate how emerging workloads interact with AI accelerator architectures and system infrastructure. The ideal candidate combines hands-on experience building large-scale AI systems with strong performance engineering skills and a solid understanding of AI accelerator architecture. You should be comfortable working across the full stack-from application frameworks and serving systems to runtime software, networking, memory systems, and accelerator hardware.You will work closely with hardware architects, systems engineers, and software researchers to understand the performance implications of emerging workloads such as agentic AI, long-context reasoning, disaggregated inference, and Mixture-of-Experts models. Your analysis will help shape future hardware-software co-design decisions and guide the development of next-generation AI infrastructure.

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

What You'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 hardware-software co-design for next-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 working 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 system-level bottlenecks.
  • Hands-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 large-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, TensorRT-LLM, DeepSpeed, Ray, or Megatron-LM.
  • Strong analytical and problem-solving skills.

#LI-VL1

What We Offer
The pay range below is for all roles at this level across all US locations and functions. Paywithin this range varies by work locationand may also depend on job-related knowledge, skills,and experience. We also offer incentive opportunities that reward employees based on individual and company performance.
This is in addition to our diverse package of benefits centered around the wellbeing of our employees and their loved ones. In addition to the usual Medical/Dental/Vision/401k, our inclusive rewards plan empowers our people to care for their whole selves. An investment in your future is an investment in ours.

Give Back With a charitable giving match and frequent opportunities to get involved, we take an active role in supporting the community.
Enjoy Time Away You'll start with 4+ weeks of paid time off a year, plus holidays and sick leave, to rest and recharge.
Care for Family Whatever family means to you, we want to support you along the way-including a stipend for fertility care or adoption, medical travel support, and virtual vet care for your fur babies.
Prioritize Emotional Wellness With on-demand apps and free confidential therapy sessions, you'll have support no matter where you are.
Stay Fit Eating well and being active are important parts of a healthy life. Our onsite Cafe and gym, plus virtual classes, make it easier.
Embrace Flexibility Benefits are best when you have the space to use them. That's why we facilitate a flexible environment so you can find the right balance for you.

Base Pay Range
$138,000—$206,000 USD

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, long-term conditions, neurodivergent individuals, or those requiring pregnancy-related support. All candidates scheduled for an interview will receive guidance on requesting accommodations.

Our Commitment to Innovation and Fairness

At Samsung Semiconductor, we use Artificial Intelligence (AI) tools in the recruitment process to enhance efficiency. However, AI is used as a support tool, not a final decision-maker. All hiring decisions are made by our human recruiting team and hiring managers to ensure every candidate is evaluated fairly and holistically.

Recruiting Agency Policy

We do not accept unsolicited resumes. Only authorized recruitment agencies that have a current and valid agreement with Samsung Semiconductor, Inc. are permitted to submit resumes for any job openings.

Applicant AI Use Policy

At Samsung Semiconductor, we support innovation and technology. However, to ensure a fair and authentic assessment, we ask that candidates rely on their own knowledge and skills throughout the process. AI tools may be used for basic preparation, grammar, and research, but should not be used to generate or assist with submitted content or live interview responses. If we determine that AI is being used outside these guidelines, we reserve the right to pause or end the interview, and your candidacy may be disqualified.

Trade Secret Notice

By submitting an application, you agree not to disclose to Samsung-or encourage Samsung to use-any confidential or proprietary information (including trade secrets) belonging to a current or former employer or other entity.

Applicant Privacy Policy
https://semiconductor.samsung.com/about-us/careers/us/privacy/

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