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Remote App Optimization Jobs in California (NOW HIRING)

Hercules

SEO Content Writer

San Francisco, CA · On-site +1

$100K - $250K/yr

Identify the highest-value keywords and search opportunities to target * e.g. "best AI app builder ... Is Hercules in-office or remote? Hercules founding team works in-office in San Francisco (Kearny ...

Lorven Technologies

Android Developer - Remote

San Jose, CA · On-site +1

$60.50 - $79.50/hr

Remote (Need to work in PST TIme Zone) Duration: 12+ months Role Overview: We are looking for an ... app performance and track errors using DataDog, ensuring optimal reliability and stability. • ...

Surefront

$129K - $168K/yr

Surefront is a cloud-based collaboration app built to bring retailers and suppliers together ... optimization * Collaborating with the front-end developers and other team members to establish ...

Surefront

You will regularly collaborate with the engineering leadership and product team to ensure optimal ... based collaboration app built to bring retailers and suppliers together through Unified ...

Zoo

Senior Software Engineer, Frontend

Los Angeles, CA · On-site +1

... remote graphics engine. This is a "back of the front-end" role, where your efforts will be ... Enhance the app's UI/UX by leveraging Typescript, React, and XState, ensuring that the interface is ...

Enara Health

Remote Nutrition Specialist

San Mateo, CA · On-site +1

$30 - $40/hr

... to be optimized and delivered in a series of personalized and programmable experiences. Our ... Ability to manage a large patient load and multiple platforms both in face to face and app ...

Enara Health

Remote Nutrition Specialist

San Mateo, CA · Remote

$30 - $40/hr

... to be optimized and delivered in a series of personalized and programmable experiences. Our ... Ability to manage a large patient load and multiple platforms both in face to face and app ...

Stretto, Inc.

Demand Generation Manager

Irvine, CA · Remote

$110K/yr

This is a remote role that can be based anywhere in the United States. Essential Functions ... Own on-page and technical SEO across our web properties, including page optimization, metadata, and ...

Zoo

Senior Software Engineer, Frontend

Los Angeles, CA · On-site +1

$145K - $195K/yr

We are headquartered in Los Angeles, CA with both a local and remote team. We were founded and ... Enhance the app's UI/UX by leveraging Typescript, React, and XState, ensuring that the interface is ...

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All JobsApp Optimization JobsRemote App Optimization JobsRemote App Optimization Jobs in California

Remote App Optimization information

What is remote app optimization?

Remote app optimization refers to the process of improving the performance, usability, and efficiency of applications that are accessed remotely, such as cloud-based or virtual applications. This involves techniques like reducing load times, optimizing network usage, enhancing security, and ensuring smooth user experiences across various devices and locations. Professionals in this field analyze app performance metrics, troubleshoot bottlenecks, and implement updates or configurations to achieve optimal app functioning for remote users.

What are some common challenges faced by professionals in remote app optimization roles, and how can they be addressed?

Professionals in Remote App Optimization often encounter challenges such as limited access to live user environments, varying device configurations, and communication barriers with distributed teams. Overcoming these issues typically involves leveraging remote testing tools, implementing automated performance monitoring, and maintaining clear, proactive communication with both development and QA teams. Staying organized and using collaborative platforms can also help ensure smooth optimization processes despite working remotely.

What are the key skills and qualifications needed to thrive as a remote app optimization specialist, and why are they important?

To thrive as a Remote App Optimization Specialist, you need a solid understanding of app performance metrics, user experience (UX) principles, and mobile analytics, often supported by a degree in computer science or related fields. Familiarity with tools like Google Analytics, Firebase, A/B testing platforms, and App Store Optimization (ASO) software is typically required. Strong analytical thinking, effective communication, and problem-solving abilities help you identify issues and collaborate with distributed teams. These skills are essential for enhancing app usability, increasing user engagement, and driving business growth in a remote work environment.

What is the difference between Remote App Optimization vs Remote Software Tester?

AspectRemote App OptimizationRemote Software Tester
Required CredentialsKnowledge of app performance, user experience, analytics toolsTesting certifications, QA training, scripting skills
Work EnvironmentCollaborates with developers, product teams, remotelyTests software, reports bugs, works with development teams remotely
Industry UsageApp development, tech companies, startupsSoftware development, quality assurance, IT firms
Search & Comparison IntentOptimizing app performance remotelyTesting software remotely, QA roles

Remote App Optimization focuses on enhancing app performance and user experience through analytics and performance tools, often collaborating with developers. Remote Software Testers primarily identify bugs and ensure software quality through testing processes. While both roles work remotely within tech industries, their core responsibilities differ: optimization centers on improving existing apps, whereas testing emphasizes quality assurance before release.

What does a remote app optimizer do?

A remote app optimizer improves the performance, usability, and efficiency of mobile or web applications by analyzing user interactions, identifying issues, and implementing enhancements. They often use tools like analytics platforms and testing software to ensure apps run smoothly across devices and networks, supporting a better user experience. Strong problem-solving skills and knowledge of app development or testing are essential for this role.

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

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

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

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

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

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

What cities in California are hiring for Remote App Optimization jobs?

Cities in California with the most Remote App Optimization job openings:

Remote App Optimization jobs near you
Infographic showing various Remote App Optimization job openings in California as of August 2026, with employment types broken down into 56% Full Time, 36% Part Time, 2% Temporary, and 6% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution.

Senior Principal Machine Learning Engineer - Optimization

PubMatic

Redwood City, CA • On-site, Remote

$153K - $211K/yr

Full-time

Medical, Dental, Vision, Life, PTO

Re-posted 23 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.
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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

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