Machine Learning Scientist 5 - Ads Demand Science
Remote, OR, US
- Pay
$466,000–750,000/yearAnnual period assumed · Location-specific pay — pay source
* Advanced degree (PhD or Master's) in Computer Science, Statistics, Mathematics, or a related quantitative field. * Experience building and shipping ML models or systems in production. * Curious and motivated to learn across ML domains, not attached to a single specialty. * Strong collaborator who's energized by building alongside others, not just independently. * Comfortable with ambiguity, able to take ownership with minimal oversight. * Proficient in Python and SQL. * Enthusiastic about and compatible with Netflix culture. 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
Read the full posting- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingDesign and ship production ML models and conversational AI agents for media planning
Build systems that evaluate and improve agent and model decision quality
Partner with scientists and engineers to ship new media planning capabilities
Take ambiguous problems from idea to production
Iterate on launched models and agents using performance data and seller feedback
From the employer’s posting
Design and ship production ML models and conversational AI agents that parse advertiser requests
Build and evolve the systems that evaluate and improve agent and model decision quality over time.
Partner with scientists and engineers across the media planning recommendation and agent workstreams
Dig into ambiguous problems, propose approaches, and drive them from idea to production.
Iterate on launched models and agents based on performance data and seller feedback.
What you’ll bring
All qualificationsCore experience
- Advanced degree (PhD or Master's) in CS, Statistics, Math, or related quantitative field
- Experience building and shipping ML models or systems in production
- Proficient in Python and SQL
- Comfortable working with ambiguity and taking ownership with minimal oversight
Preferred experience
- Experience with operations research
- Experience with AI engineering or agentic systems
Qualification wording
Advanced degree (PhD or Master's) in Computer Science, Statistics, Mathematics, or a related quantitative field.
Experience building and shipping ML models or systems in production.
Proficient in Python and SQL.
Comfortable with ambiguity, able to take ownership with minimal oversight.
Experience with operations research.
Experience with AI engineering or agentic systems.
Education & alternatives
Who You Are: * Advanced degree (PhD or Master's) in Computer Science, Statistics, Mathematics, or a related quantitative field. * Experience building and shipping ML models or systems in production. * Curious and motivated to learn across ML domains, not attached to a single specialty. * Strong collaborator who's energized by building alongside others, not just independently. * Comfortable with ambiguity, able to take ownership with minimal oversight. * Proficient in Python and SQL. * Enthusiastic about and compatible with Netflix culture. 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.
Tools in this posting
- Python
- SQL
Source — Tool mentions in context
Who You Are: * Advanced degree (PhD or Master's) in Computer Science, Statistics, Mathematics, or a related quantitative field. * Experience building and shipping ML models or systems in production. * Curious and motivated to learn across ML domains, not attached to a single specialty. * Strong collaborator who's energized by building alongside others, not just independently. * Comfortable with ambiguity, able to take ownership with minimal oversight. * Proficient in Python and SQL. * Enthusiastic about and compatible with Netflix culture. 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.
Posting record
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- Live
- First seen by us
- Oct 6, 2026 · 24 days ago
- Recorded sightings
- 104
- Last seen by us
- Oct 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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- 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.
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Remote, OR, US
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