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Performance Optimization Jobs in California (NOW HIRING)

Apple

SW Optimization Engineer AI/ML

Cupertino, CA · On-site

$172K/yr

Our team is driving performance enhancements in application and system software and developing novel algorithms to deliver integrated, highly optimized solutions based on Apple Silicon. Description ...

New

Genmo

GPU Performance Engineer

San Francisco, CA · On-site

The Role You'll be our performance optimization expert, using advanced profiling tools to identify bottlenecks and implementing solutions that achieve 5-10x speedups. From writing custom CUDA kernels ...

Genmo

GPU Performance Engineer

San Francisco, CA · On-site

The Role You'll be our performance optimization expert, using advanced profiling tools to identify bottlenecks and implementing solutions that achieve 5-10x speedups. From writing custom CUDA kernels ...

Qualcomm

Windows Performance Engineer, Staff

San Diego, CA · On-site

$134.80 - $202.20/hr

General Summary Qualcomm is looking for an experienced Windows Power/Performance Developer with passion for analyzing and optimizing software running on Windows on Snapdragon. The senior developer ...

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Performance Optimization information

What are the key skills and qualifications needed to thrive in performance optimization?

To excel in Performance Optimization, you need a strong analytical mindset, expertise in data interpretation, and a relevant degree in fields like engineering, computer science, or business analytics. Familiarity with tools such as SQL, Python, Tableau, and process improvement methodologies like Lean or Six Sigma is often required. Excellent problem-solving, communication, and project management skills set standout candidates apart. These abilities are essential for identifying improvement opportunities and effectively driving process enhancements within an organization.

What are some common challenges faced in a performance optimization role, and how are they typically addressed?

Professionals in Performance Optimization often encounter challenges such as managing complex data sets, aligning diverse teams around process changes, and quantifying the impact of optimizations. Overcoming these hurdles usually involves effective stakeholder communication, strong analytical processes, and the use of advanced data visualization tools to make insights actionable. Teams often collaborate closely with IT, operations, and management to ensure solutions are both technically sound and practical. Regular training and adapting to new industry best practices help maintain high performance and continue driving meaningful improvements.

What is a performance optimization?

A Performance Optimization job focuses on analyzing, improving, and maintaining the efficiency of systems, processes, or applications. Professionals in this role identify bottlenecks, implement solutions, and enhance overall performance using data-driven strategies. They may work with software, business processes, or operational workflows to maximize productivity and resource utilization. This role often requires expertise in analytics, problem-solving, and technical tools specific to the industry.

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

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

What are popular job titles related to Performance Optimization jobs in California?

For Performance Optimization jobs in California, the most frequently searched job titles are:

What job categories do people searching Performance Optimization jobs in California look for?

The top searched job categories for Performance Optimization jobs in California are:

Performance Optimization jobs near you
Infographic showing various Performance Optimization 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.

Principal ML Engineer - Large Scale Training Performance Optimization

Advanced Micro Devices, Inc

San Jose, CA • On-site

$210K/yr

Full-time

Re-posted 26 days ago

Advanced Micro Devices rating

8.6

Company rating: 8.6 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

27th of 157 rated electronics manufacturers

Job description

WHAT YOU DO AT AMD CHANGES EVERYTHING
At AMD, our mission is to build great products that accelerate next-generation computing experiences-from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you'll discover the real differentiator is our culture. We push the limits of innovation to solve the world's most important challenges-striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.
THE ROLE:
We are looking for a Principal Machine Learning Engineer to join our Models and Applications team. If you are excited by the challenge of distributed training of large models on a large number of GPUs, and if you are passionate about improving training efficiency while innovating and generating new ideas, then this role is for you. You will be part of a world class team focused on addressing the challenge of training generative AI at scale.
THE PERSON:
The ideal candidate should have experience with distributed training pipelines, be knowledgeable in distributed training algorithms (Data Parallel, Tensor Parallel, Pipeline Parallel, Expert Parallel ZeRO), and be familiar with training large models at scale.
KEY RESPONSIBILITIES:
  • Train large models to convergence on AMD GPUs at scale.
  • Improve the end-to-end training pipeline performance.
  • Optimize the distributed training pipeline and algorithm to scale out.
  • Contribute your changes to open source.
  • Stay up-to-date with the latest training algorithms.
  • Influence the direction of AMD AI platform.
  • Collaborate across teams with various groups and stakeholders.

PREFERRED EXPERIENCE:
  • Experience with ML/DL frameworks such as PyTorch, JAX, or TensorFlow.
  • Experience with distributed training and distributed training frameworks, such as Megatron-LM, MaxText, TorchTitan.
  • Experience with LLMs or computer vision, especially large models, is a plus.
  • Experience with GPU kernel optimization is a plus.
  • Excellent Python or C++ programming skills, including debugging, profiling, and performance analysis at scale.
  • Experience with ML infra at kernel, framework, or system level
  • Strong communication and problem-solving skills.

ACADEMIC CREDENTIALS:
  • A master's degree or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

LOCATION:
  • San Jose, CA or Bellevue, WA preferred. May consider other US markets within proximity of US AMD offices.

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Benefits offered are described: AMD benefits at a glance.
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants' needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD's "Responsible AI Policy" is available here.
This posting is for an existing vacancy.

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