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Machine Learning Teaching Remote Jobs in Mountain View, CA

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Machine Learning Teaching Remote information

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$27.1K

$63.1K

$117.4K

How much do machine learning teaching remote jobs pay per year?

As of Aug 20, 2026, the average yearly pay for machine learning teaching remote in Mountain View, CA is $63,084.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,700.00 and $70,800.00 per year, depending on experience, location, and employer.

What is a machine learning teaching remote?

A Machine Learning Teaching Remote job involves instructing students or professionals on machine learning concepts and techniques through online platforms. Educators in this role design and deliver course materials, lead virtual lectures or workshops, and provide feedback on assignments. The position typically allows for flexible work from home and may include mentoring, curriculum development, and staying updated with the latest trends in machine learning. It is ideal for those with expertise in machine learning and a passion for teaching, who are comfortable using digital communication tools.

What are the main challenges of teaching machine learning remotely, and how can they be addressed?

One of the main challenges of teaching machine learning remotely is ensuring student engagement and comprehension, especially with complex concepts and hands-on programming tasks. In a remote setting, it's important to leverage interactive tools, frequent check-ins, and collaborative platforms to maintain student participation and provide timely feedback. Additionally, clear communication and well-structured materials help bridge the gap that physical presence often fills. Successful remote instructors often schedule virtual office hours and foster online discussion forums to support students effectively.

What are the key skills and qualifications needed to thrive as a machine learning teaching remote, and why are they important?

To thrive as a remote Machine Learning Teacher, you need a strong grasp of machine learning concepts, algorithms, and programming (often with a background in computer science or a related field). Familiarity with tools such as Python, Jupyter Notebooks, TensorFlow, and relevant online teaching platforms or Learning Management Systems is essential. Excellent communication, patience, and the ability to explain complex concepts clearly are vital soft skills for engaging remote learners. These skills ensure that students receive high-quality instruction and support, making advanced topics accessible and fostering effective learning in a virtual environment.

What are popular job titles related to Machine Learning Teaching Remote jobs in Mountain View, CA?

For Machine Learning Teaching Remote jobs in Mountain View, CA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Teaching Remote jobs in Mountain View, CA look for?

The top searched job categories for Machine Learning Teaching Remote jobs in Mountain View, CA are:

What cities near Mountain View, CA are hiring for Machine Learning Teaching Remote jobs?

Cities near Mountain View, CA with the most Machine Learning Teaching Remote job openings:

Infographic showing various Machine Learning Teaching Remote job openings in Mountain View, CA as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 26% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $63,084 per year, or $30.3 per hour.

Senior Principal Machine Learning Engineer - Optimization

PubMatic

Redwood City, CA โ€ข On-site, Remote

$153K - $211K/yr

Full-time

Medical, Dental, Vision, Life, PTO

Re-posted 26 days ago


Job description

Role: Hybrid in Redwood City, CA. (Will consider Remote for the right candidate)

Must have:ย 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.ย 

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:ย 

    • 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.ย 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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