Machine Learning Scientist 4 - Content & Conversation Modeling

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.

The Content & Conversation Modeling team delivers high-leverage ML solutions using Netflix’s unique media data, driving decisions across content strategy, acquisition, scheduling, and advertising. Our models are used to predict engagement, forecast title performance, assess catalog strength, and so much more. We are looking for a senior machine learning scientist to develop, optimize, and deploy scalable ML solutions that power content decisions at Netflix. 

• 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 engineer, ML Ops, and ML Platform teams. 

• Live Netflix values while bringing a new perspective to continue improving our culture.

• An 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.

• A passion for scaling your ML solutions in collaboration with your team. You 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.

• An appreciation of the creative and entertainment industry is definitely a plus.
   

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.

Netflix is a unique culture and environment. Learn more here.

Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. 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.

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.