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How much do performance optimization jobs pay per year?

As of Jun 1, 2026, the average yearly pay for performance optimization in the United States is $68,249.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,000.00 and $83,000.00 per year, depending on experience, location, and employer.

What is a Performance Optimization job?

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 key skills and qualifications needed to thrive in the Performance Optimization position, and why are they important?

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.
More about Performance Optimization jobs
What cities are hiring for Performance Optimization jobs? Cities with the most Performance Optimization job openings:
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What states have the most Performance Optimization jobs? States with the most job openings for Performance Optimization jobs include:
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Performance Optimization jobs near you
Infographic showing various Performance Optimization job openings in the United States as of May 2026, with employment types broken down into 40% Full Time, and 60% Part Time. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution, with an average salary of $68,249 per year, or $32.8 per hour.

Senior/Staff Software Engineer, ML Performance Optimization

Zoox

Foster City, CA • On-site

$142.80K - $188.20K/yr

Full-time

Posted 18 days ago

Job description

Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in large-scale Foundation models, VLMs, and VLAs to make autonomous driving as seamless as possible. 
 
The Opportunity
Are you excited to drive our ML Performance Optimization initiatives and make our ML models that enable autonomous driving as fast and efficient as possible? You will get to work with SOTA accelerators, cutting-edge techniques in distributed training, quantization, distillation, and pruning, among other things, working closely with all the Autonomy teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox.
 
model development, and serving systems that our applied research teams use for in- and off-vehicle ML use cases. You will work alongside a team of strong software engineers and act as a force multiplier for our internal customers. This team has many growth opportunities as we expand our robotaxi deployments and venture into new ML domains. If you want to learn more about our stack behind autonomous driving, please look here. If you want to learn more about our ML Infrastructure, here is one of our past talks at re:Invent.
In this role, you will:
  • Develop and execute a strategic vision for the ML Performance Optimization team to unlock ML innovation in autonomous driving and rider experience. 
  • Lead the design, implementation, and operation of cutting-edge ML Training OR Inference performance optimization techniques to scale our VLM, VLA, and Foundational models and deploy them efficiently in our robotaxi.
  • Collaborate closely with x-functional teams, including ML researchers, software engineers, data engineers, and hardware engineers, to define requirements and align on architectural decisions.
  • Enable the engineers in the team to grow their careers by providing technical guidance and mentorship.
Qualifications

Note: You do not have to meet all the requirements below to be considered for this position:

  • Strong experience with training frameworks like PyTorch, leveraging GPUs efficiently for distributed model training.
  • Experience with GPU-accelerated inference using TensorRT or similar frameworks.
  • Experience using profiling tools like NVIDIA's Nsight or PyTorch's Profiler for identifying model training and serving bottlenecks.
  • Proficient in Python and C++
  • Experience with model compression techniques to reduce model size and improve performance.
Bonus Qualifications
  • 10+ years of total experience, including 4+ years of working on large-scale model training or inference platforms.
  • Excellent leadership skills with a demonstrated ability to lead high-performing engineering teams.
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.

Follow us on LinkedIn

Accommodations
If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.

A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.