Netflix
Program Manager, Human Evaluations (Recommendations)
Remote, United States · Mid · Full-time
Sponsorship not specified$230k-$360kDetected 28 min ago
Machine LearningData ScienceA/B TestingProduct StrategyVendor ManagementControlsResearchCommunicationOrganizational Skills
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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.
Personalize to your clock →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 54 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
- Join a team creating the frameworks, tools, and workflows that ensure human judgment is applied with consistency, clarity, and care, whether we are evaluating relevance, repetition, diversity, or whether a recommendation simply makes sense to the member.
- From scoping and planning to vendor management, rater onboarding, and calibration, you will be accountable for driving delivery from start to finish.
- The ideal candidate brings a rare combination of structure and flexibility.
Responsibilities
- Lead end-to-end execution of human evaluation and data operations initiatives, from intake and scoping to delivery
- Partner with Product Management to translate recommendation strategy and roadmap priorities into evaluation designs, success metrics, and timelines
- Manage human annotation vendors, including capacity planning, SLAs, quality performance, and escalations
- Drive operational efficiency across evaluation programs, including cost per task, throughput, turnaround time, and speed to IRR
- Develop clear, scalable guidelines and scoring rubrics to ensure consistent rater judgment, including for subjective, taste-based questions
- Act as the connective tissue across product, ML, data science, and vendor partners to ensure alignment and effective execution of evaluations at scale
Requirements
- 4+ years of experience working in human evaluations, data collection, labeling, or annotation operations in ML environments
- Track record of implementing process improvements or quality control systems for data collection needs
- Experience improving operational efficiency of annotation programs (throughput, turnaround, cost)
- Strong understanding of evaluation design, including guidelines, rubrics, and scoring protocols
- Proven ability in end-to-end management of complex, cross-functional programs, demonstrating strong Program Management skills and clear accountability for successful delivery
- Experience with human labeling platforms
- Ability to synthesize feedback into clear recommendations and process improvements
- ability to track details while seeing the bigger picture
- You have working fluency in film and TV content and can quickly scan a set of titles to tell whether they belong together.
Nice to have
- Experience with personalization, recommender systems, search, or ranking evaluation
- Familiarity with how offline human evaluation complements online experimentation (A/B tests) and engagement metrics
- Experience evaluating at the list or page level, not only the individual item level
- Experience partnering with Product Managers and Data Scientists on metric definition
- we do not have bonuses.
- 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 $230,000.00 - $360,000.00.
- Netflix is a unique culture and environment.
Compensation
- $230k-$360k
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.
- Netflix is building toward more relevant, more varied, and more trustworthy recommendations, and thoughtful, high-quality evaluation is essential to making sure we are moving in the right direction.
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This listing is sourced directly from Netflix's careers page and normalized into a canonical job model.