Netflix

Netflix

AI Research Scientist 4/5 - Generative Models, Recommender Systems

Remote, United States · Full-time

Sponsorship not specified$300k-$537kDetected 13 days ago
Machine LearningDeep LearningNLPLLMsResearch

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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 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 Promotional Assets & Creative Technology AIMS team is at the forefront of Netflix's efforts to effectively promote titles and enhance the content discovery experience.
  • In this rare opportunity, you will have the chance to define the direction for algorithmic strategies and spearhead the execution of ML solutions and ultimately shape how titles are promoted on Netflix and discovered by our members.
  • The range for this role is $300,000.00 - $537,000.00.

Responsibilities

  • Apply state-of-the-art techniques to high-impact problems such as summarization quality and building LLM-based evaluators ("judges") that assess whether generated content meets quality bars.
  • Lead end-to-end ML development on these problems: research, model training, and evaluation.
  • Optimize generated content for member impact, treating content generation and audience targeting as coupled problems - drawing on recommendation systems thinking to ensure generated assets are optimized for the members they're meant to reach.
  • Partner with ML scientists and engineers to integrate models into business applications and platforms.
  • Engage with the ML community, internal and external, to learn, to teach, and to contribute to building a great Netflix brand.

Nice to have

  • Experience with recommendation systems, personalization, or other member-facing optimization systems is a strong plus.

Compensation

  • 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.
  • Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off.

Benefits

  • Strong foundation in ML and Deep Learning, especially in Natural Language Processing / Understanding and Generation.
  • Research experience in summarization or generated-text evaluation (e.g., LLM-as-judge methods) is a big plus; background in vision models such as diffusion models is a plus.
  • We also offer paid leave of absence programs.
  • Full-time salaried employees are immediately entitled to flexible time off.
  • See more details about our Benefits here.

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.
  • Track advancements in LLM and generative model research, and translate them into concrete opportunities for the problem space we are working on.
  • Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates.
  • We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams.

Equal opportunity

  • We approach diversity and inclusion seriously and thoughtfully.
  • 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.
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This listing is sourced directly from Netflix's careers page and normalized into a canonical job model.