Netflix

Netflix

Machine Learning Scientist 5 - Ads Demand Science

Remote, United States · Full-time

Sponsorship not specified$466k-$750kDetected 23 days ago
PythonRESTMachine LearningData ScienceAgentic AIMLOpsStatistics

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odds of building a lasting career here

64Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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Employer immigration record

from this employer's Department of Labor filings

Green-card filing pattern in this occupation

Context, not a finding about this posting: of this employer's 6 green-card filings in this occupation, 100% were for a worker who already held the job.

Green-card follow-through: 85%

Of 40 labor certifications old enough to have been used, 6 expired without the employer filing the next step. Median time from filing to decision: 496 days.100% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.

Files H-1B transfers

160 transfer filings in the last year, covering 388 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • The Demand Science team within Ads Data Science & Engineering plays a crucial role in Netflix Ads growth by equipping the business to efficiently attract, activate, and scale advertiser demand.
  • As a machine learning scientist in Media Planning, you'll work across the ML models and AI agents that turn advertiser briefs into optimized, ready-to-buy media plans.

Responsibilities

  • Design and ship production ML models and conversational AI agents that parse advertiser requests and help sellers plan and compare media plan options.
  • 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 to ship and iterate on new capabilities.
  • Dig into ambiguous problems, propose approaches, and drive them from idea to production.

Nice to have

  • Experience with operations research.
  • Experience with AI engineering or agentic systems.
  • Advanced degree (PhD or Master's) in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • Curious and motivated to learn across ML domains, not attached to a single specialty.
  • Comfortable with ambiguity, able to take ownership with minimal oversight.
  • Proficient in Python and SQL.
  • Enthusiastic about and compatible with Netflix culture.
  • we do not have bonuses.

Compensation

  • $466k-$750k

Company info

  • 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're looking for a generalist who's curious, motivated to learn, and eager to build alongside the rest of the team, not someone who's already settled into one corner of ML.
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This listing is sourced directly from Netflix's careers page and normalized into a canonical job model.