Machine Learning Scientist 4 - Content & Conversation ModelingNetflix • Seattle, Washington, United States

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Machine Learning Scientist 4 - Content & Conversation Modeling

Netflix

Seattle, Washington, United States

Seattle, Washington, United States

Jetzt Bewerben

Über

At Netflix, our mission is to entertain the world. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting‑edge technology. The Content & Conversation Modeling team delivers high‑leverage machine learning solutions using Netflix’s unique media data, driving decisions across content strategy, acquisition, scheduling, and advertising. Our models predict engagement, forecast title performance, assess catalog strength, and more. We are looking for a senior machine learning scientist to develop, optimize, and deploy scalable ML solutions that power content decisions at Netflix. Responsibilities Innovate on a suite of predictive models to help inform our content strategy. Be a thought partner with our content strategy teams as we continue to evolve our approach to content valuation, scheduling, and performance. Partner closely with our analytics teams as they leverage our models on the ground both in the US and globally. Own the end-to-end ML model development lifecycle, from ideation and feature engineering to model training, evaluation, deployment, monitoring, and continuous improvement. Inform and influence data and ML infrastructure development through partnership with data engineering, ML Ops, and ML Platform teams. Qualifications Ability to navigate ambiguous problem spaces with a passion for translating them into practical technical solutions, including a track record of delivering business solutions leveraging machine learning. Exceptional communication skills, able to explain complex technical concepts clearly to cross‑functional partners with differing technical backgrounds. Deep familiarity with the ML lifecycle and strong technical judgment when assessing different solutions for deploying models in production. Passion for scaling your ML solutions in collaboration with your team; seek to build modularly, for resilience, and in ways where others can take on your code when you’re away. Strong experience in Python and a ML/DL framework (e.g., scikit‑learn, Keras, PyTorch, TensorFlow, MetaFlow, JAX). An advanced degree (MS or PhD) in Computer Science, Economics, Physics, Statistics, Mathematics, or a related technical field with a focus on machine learning and predictive modeling. Relevant experience in one or more machine learning roles. Appreciation of the creative and entertainment industry is definitely a plus. Compensation & Benefits 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. The range for this role is $300,000.00 – $537,000.00. Health Plans Mental Health support 401(k) Retirement Plan with employer match Stock Option Program Disability Programs Health Savings and Flexible Spending Accounts Family‑forming benefits Life and Serious Injury Benefits Paid leave of absence programs Full‑time hourly employees accrue 35 days annually for paid time off (vacation, holidays, sick). Full‑time salaried employees are immediately entitled to flexible time off. Equal Opportunity Statement 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.
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Seattle, Washington, United States

Sprachkenntnisse

English

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