Back to jobs

Machine Learning Scientist 5 - Ad Ranking

Remote, OR, US; New York, NY, US; Los Angeles, CA, US; Los Gatos, CA, US

Pay
$466,000–750,000/yearAnnual period assumed · Location-specific pay — pay source
* Excellent communication and collaboration skills. Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $466,000.00 - $750,000.00. This compensation range will vary based on location. Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.
Read the full posting
Work setting
Remote — work setting source
Listed location: Remote, OR,US; New York, NY,US; Los Angeles, CA,US; Los Gatos, CA,US
Read the full posting
Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
Apply at Netflix

What you’ll work on

Full posting
  • Design and implement machine learning and optimization algorithms for ad quality and performance

  • Build, train, and evaluate models on large-scale production data

  • Develop online and offline evaluation frameworks to measure model impact

  • Define optimization objectives and trade-offs with the product team

  • Communicate technical decisions and experiment results to technical and non-technical stakeholders

From the employer’s posting
Design and implement machine learning and optimization algorithms to improve ad quality and performance.
Build, train, and evaluate models on large-scale production data.
Develop online and offline evaluation frameworks to rigorously measure the impact of model and algorithm improvements.
Partner closely with the product team to define optimization objectives, constraints, and trade-offs that align with product and business goals.
Communicate technical decisions, trade-offs, and experiment results to both technical and non-technical stakeholders
Education & alternatives
## Qualifications: * Advanced degree (PhD or Master’s) in Computer Science, Statistics, Mathematics, or related quantitative field. * Proficiency in Python, Scala or Java.

Tools in this posting

  • Java
  • Python
  • Scala
Source — Tool mentions in context
* Advanced degree (PhD or Master’s) in Computer Science, Statistics, Mathematics, or related quantitative field. * Proficiency in Python, Scala or Java. * Deep knowledge of machine learning, optimization, and data analysis techniques.

Posting record

Report an error

Open 4 monthsWe first saw this posting 120 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Jul 1, 2026 · 120 days ago
Recorded sightings
322
Last seen by us
Oct 30, 2026
Employer says posted
Apr 7, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

Your next step

  • Have your resume and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.

Complete your application on explore.jobs.netflix.net. The employer’s form will show what is required.

Already applied? Track this application

Job description

View original posting ↗

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next. We launched a new ad-supported tier in November 2022 and are building an in-house world-class ad tech ecosystem to offer our members more choices in consuming their content. Our new tier allows us to attract new members at a lower price point while also creating a compelling path for advertisers to reach deeply engaged audiences. ## Our Team: The Ad Ranking team within the Ads Data Science and Engineering organization is the central intelligence driving ad personalization at Netflix. The team is responsible for enhancing ad quality and performance through advanced machine learning and optimization algorithms, utilizing both proprietary and external data signals. Key areas of focus include Identity Science, User Understanding, Audience & Targeting, Relevance & Engagement Prediction, and Bidding & Pacing. Our goal is to create innovative, data-driven solutions that deliver highly relevant ad experiences for our members and achieve impactful results for advertisers, all while upholding the exceptional quality and personalization characteristic of the Netflix experience. ## Responsibilities: * Design and implement machine learning and optimization algorithms to improve ad quality and performance. * Build, train, and evaluate models on large-scale production data. * Develop online and offline evaluation frameworks to rigorously measure the impact of model and algorithm improvements. * Partner closely with the product team to define optimization objectives, constraints, and trade-offs that align with product and business goals. * Communicate technical decisions, trade-offs, and experiment results to both technical and non-technical stakeholders, driving understanding and adoption of ML-driven solutions. ## Qualifications: * Advanced degree (PhD or Master’s) in Computer Science, Statistics, Mathematics, or related quantitative field. * Proficiency in Python, Scala or Java. * Deep knowledge of machine learning, optimization, and data analysis techniques. * Experience with prototyping and deploying algorithms using large-scale production data. * Strong business acumen and ability to translate technical results into business impact. * Experience in ad optimization stack, e.g. targeting, ranking, bidding.. * Excellent communication and collaboration skills. Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $466,000.00 - $750,000.00. This compensation range will vary based on location. Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here. Netflix is a unique culture and environment. Learn more here. Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner. We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. Job is open for no less than 7 days and will be removed when the position is filled.
Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay
* Excellent communication and collaboration skills. Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $466,000.00 - $750,000.00. This compensation range will vary based on location. Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.
Location & working pattern

Remote, OR, US; New York, NY, US; Los Angeles, CA, US; Los Gatos, CA, US

Working pattern and location restrictions need checking in the full posting.

Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

See how this role fits your experience

Add your resume to compare the role’s scope, tools and requirements with your experience.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.