ZipRecruiter

Log In

2

Remote Performance Optimization Jobs in Santa Clara, CA

Snarkify

Senior Software Engineer - CUDA

Palo Alto, CA · On-site +1

$144K - $189K/yr

Your expertise in GPU computing, performance optimization, and parallel programming will be ... A flexible and innovative remote work environment. * Room for continuous growth and development in ...

Snarkify

Senior Software Engineer - CUDA

Palo Alto, CA · On-site +1

$144K - $189K/yr

Your expertise in GPU computing, performance optimization, and parallel programming will be ... A flexible and innovative remote work environment. * Room for continuous growth and development in ...

Broadcom

AI Systems Performance Engineer

San Jose, CA · Remote

$141K - $226K/yr

Fabric Optimization: Tune and optimize network parameters, focusing heavily on Ethernet fabric ... Experience with RDMA (Remote Direct Memory Access) and RoCEv2 (RDMA over Converged Ethernet)

Cyngn

Senior C++ Robotics Engineer

Mountain View, CA · Remote

$198K - $225K/yr

Your expertise in robotics, system administration, and performance optimization will be crucial in ... Monthly meal and tech allowances for remote employees *Please note salary range is for Bay Area ...

next page

Showing results 1-20

All JobsPerformance Optimization JobsRemote Performance Optimization JobsRemote Performance Optimization Jobs in Santa Clara, CA

Remote Performance Optimization information

See Santa Clara, CA salary details

$12

$70

$115

How much do remote performance optimization jobs pay per hour?

As of Jul 29, 2026, the average hourly pay for remote performance optimization in Santa Clara, CA is $70.59, according to ZipRecruiter salary data. Most workers in this role earn between $57.88 and $79.90 per hour, depending on experience, location, and employer.

What is the difference between Remote Performance Optimization vs Remote Performance Analyst?

AspectRemote Performance OptimizationRemote Performance Analyst
Primary FocusImproving overall system, application, or website performance through technical strategiesAnalyzing performance data to identify issues and recommend improvements
Required SkillsTechnical expertise in performance tuning, coding, and system architectureData analysis, reporting, and troubleshooting skills
Work EnvironmentCollaborates with developers, IT teams, and stakeholders on performance projectsWorks with data sets, monitoring tools, and reports to assess performance
Common UsageUsed by companies aiming to optimize their digital assets' speed and efficiencyUsed by organizations to monitor and analyze system performance metrics

While both roles focus on performance, Remote Performance Optimization involves proactive technical improvements, whereas Remote Performance Analyst emphasizes analyzing data to inform performance strategies. Understanding these differences helps organizations assign the right talent for their performance needs.

What are popular job titles related to Remote Performance Optimization jobs in Santa Clara, CA? For Remote Performance Optimization jobs in Santa Clara, CA, the most frequently searched job titles are:
What job categories do people searching Remote Performance Optimization jobs in Santa Clara, CA look for? The top searched job categories for Remote Performance Optimization jobs in Santa Clara, CA are:
What cities near Santa Clara, CA are hiring for Remote Performance Optimization jobs? Cities near Santa Clara, CA with the most Remote Performance Optimization job openings:
Remote Performance Optimization jobs near you
Infographic showing various Remote Performance Optimization job openings in Santa Clara, CA as of July 2026, with employment types broken down into 87% Full Time, 10% Part Time, and 3% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $146,827 per year, or $70.6 per hour.
Senior Principal Machine Learning Engineer - Optimization

Senior Principal Machine Learning Engineer - Optimization

PubMatic

Redwood City, CA • On-site, Remote

$153K - $211K/yr

Full-time

Medical, Dental, Vision, Life, PTO

Posted 6 days ago

Job description

Role: Hybrid in Redwood City, CA. (Will consider Remote for the right candidate)
Must have: Experience building large-scale prediction or optimization systems
PubMatic is the leading AI-powered ad tech company delivering measurable advertising performance through an intelligent, unified platform that connects buyers, publishers, data partners, and commerce media across CTV, mobile app, and omnichannel environments.
About the Role:
We are looking for a Senior Principal Machine Learning Engineer to help build the next generation of performance optimization capabilities for PubMatic's Activate platform.
This role is focused on applying machine learning, prediction, ranking, calibration, experimentation, and optimization techniques to improve campaign outcomes across performance advertising goals such as CTR, VCR, CPC, CPA, and ROAS. The ideal candidate has strong ML fundamentals and experience building large-scale production models or optimization systems.
What You'll Do:
  • Build and improve machine learning models for campaign optimization, prediction, ranking, bidding, forecasting, and calibration.
  • Develop models and algorithms that improve advertiser outcomes while balancing spend delivery, cost efficiency, campaign goals, marketplace dynamics, and system constraints.
  • Work on large-scale ML systems using signals from auctions, impressions, clicks, video events, conversions, users, context, inventory, campaigns, and marketplace feedback.
  • Design and improve CTR, CVR, VCR, CPA, ROAS, app-install, user-value, and campaign-performance models.
  • Develop bidding, pacing-aware optimization, ranking, exploration, and value-estimation approaches for performance advertising.
  • Improve model calibration, online/offline evaluation, experimentation, observability, and production feedback loops.
  • Reason through sparse conversions, delayed feedback, biased logs, cold-start campaigns, attribution noise, and online/offline metric mismatch.
  • Partner with performance advertising signal engineers to define model-ready features, labels, attribution windows, negative examples, training datasets, and online serving requirements.
  • Partner with engineering, product, analytics, and platform teams to translate model outputs into real-time decisioning systems.
  • Help evolve Activate from a media buying execution platform into a performance optimization platform.
  • Provide technical leadership and mentorship to engineers and applied scientists working on performance optimization problems.
  • 10+ years of experience building production machine learning, ranking, recommendation, prediction, optimization, ads, marketplace, bidding, or pricing systems.
  • Strong understanding of supervised learning, ranking, calibration, causal thinking, experimentation, statistical evaluation, and model monitoring.
  • Experience building large-scale prediction or optimization systems in production.
  • Experience with CTR/CVR prediction, conversion modeling, bid optimization, value modeling, forecasting, calibration, or performance optimization.
  • Strong ability to reason about model quality, business impact, system constraints, production tradeoffs, and online performance.
  • Experience working with large-scale data and distributed ML workflows.
  • Strong engineering skills in Python, Java, SQL, Spark, TensorFlow, PyTorch, XGBoost, or similar technologies.
  • Ability to provide technical leadership across ambiguous, high-impact optimization problems.
  • BS, MS, or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Engineering, or a related technical field.

Preferred Experience:
    • Experience in ads, search, recommendations, marketplaces, e-commerce, fintech, pricing, bidding, or real-time optimization systems.
    • Experience with performance advertising goals such as CTR, VCR, CPC, CPA, ROAS, app install, retargeting, or user-value optimization.
    • Familiarity with real-time bidding, programmatic advertising, ad serving, attribution, pacing, identity, incrementality, or performance advertising.
    • Experience with exploration/exploitation, counterfactual evaluation, uplift modeling, delayed-feedback modeling, or learning under biased logs.
    • Experience with model calibration, model observability, A/B testing, online experimentation, incrementality testing, or lift measurement.
    • Experience working cross-functionally with product, engineering, analytics, and business stakeholders.

We'd love for you to have:
  • 10+ years of experience building production machine learning, ranking, recommendation, prediction, optimization, ads, marketplace, bidding, or pricing systems.
  • Strong understanding of supervised learning, ranking, calibration, causal thinking, experimentation, statistical evaluation, and model monitoring.
  • Experience building large-scale prediction or optimization systems in production.
  • Experience with CTR/CVR prediction, conversion modeling, bid optimization, value modeling, forecasting, calibration, or performance optimization.
  • Strong ability to reason about model quality, business impact, system constraints, production tradeoffs, and online performance.
  • Experience working with large-scale data and distributed ML workflows.
  • Strong engineering skills in Python, Java, SQL, Spark, TensorFlow, PyTorch, XGBoost, or similar technologies.
  • Ability to provide technical leadership across ambiguous, high-impact optimization problems.
  • BS, MS, or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Engineering, or a related technical field.

Additional Information
Return to Office: PubMatic employees throughout the globe have returned to our offices via a hybrid work schedule (3 days "in office" and 2 days "working remotely") that is intended to maximize collaboration, innovation, and productivity among teams and across functions.
Benefits: Our benefits package includes the best of what leading organizations provide such as, paid leave programs, paid holidays, healthcare, dental and vision insurance, disability and life insurance, commuter benefits, physical and financial wellness programs, unlimited DTO in the US (that we actually require you to use!), reimbursement for mobile and fully stocked pantries plus in-office catered lunches 5 days per week.
Diversity and Inclusion: PubMatic is proud to be an equal opportunity employer; we don't just value diversity, we promote and celebrate it. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status
About PubMatic
PubMatic is one of the world's leading scaled digital advertising platforms, offering more transparent advertising solutions to publishers, media buyers, commerce companies and data owners, allowing them to harness the power and potential of the open internet to drive better business outcomes. Founded in 2006 with the vision that data-driven decisioning would be the future of digital advertising, we enable content creators to run a more profitable advertising business, which in turn allows them to invest back into the multi-screen and multi-format content that consumers demand.
#LI-HYBRID
Compensation Disclosure
In accordance with applicable law, the below salary range provided is PubMatic's reasonable estimate of the total compensation for this role. New hires and current team members are typically compensated toward the middle of our pay range. The actual amount may vary, based on non-discriminatory factors such as location, experience, knowledge, skills and abilities. In addition to salary PubMatic also offers a bonus, restricted stock units, and a competitive benefits package.
Total Compensation Range
$260,000-$330,000 USD

Apply