Machine Learning Engineer 5 - Content & Studio

Netflix

full-time

Posted: September 29, 2025

Number of Vacancies: 1

Job Description

Netflix is one of the world's leading entertainment services, with over 300 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.At Netflix, we seek to entertain the world. We launch thousands of new TV shows and movies every year for our members across the globe. To do so, we need to understand which shows to launch, when to launch, and for which audiences over the next months, quarters, and years to delight our current and future members.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 an experienced machine learning engineer to develop, optimize, and deploy scalable ML solutions that power content decisions at Netflix. ResponsibilitiesOwn and innovate upon ML models that predict how members engage with our content slate and future launching titles, helping inform a range of decisions across the content, studio, and advertising domains.Design, build, and deploy robust ML systems which scale to handle Netflix-sized data.Automate ML workflows for training, tuning, and deployment; enabling faster experimentation and productization.Optimize model performance and inference efficiency, ensuring scalability in high-throughput distributed environments. Improve ML observability, model evaluations, model monitoring, and debugging tools to ensure reliability of deployed models. Collaborate with scientists, data engineers, and infrastructure teams to define project roadmaps, ensure alignment of goals, and drive integration with downstream applications.Transform research prototypes into high-quality production code, ensuring systems are maintainable, scalable, and performant.Stay up to date with ML infrastructure advancements, identifying new technologies and best practices to enhance efficiency. About YouYou have a strong foundation in machine learning, including supervised and unsupervised learning, and deep learning architectures (e.g. recommendations, forecasting). You have a track record of deploying ML systems at scale, particularly in distributed training environments and high-performance inference. You have hands-on experience evaluating and monitoring machine learning systems in production.You have a strong understanding of feature engineering, data pipelines, and model lifecycle management for large-scale data processing problems using tools like Spark.You hold an advanced degree (MS or PhD) in Computer Science, Electrical Engineering, or a related technical field with a focus on machine learning or artificial intelligence.You have at least 5 years of relevant industry experience designing and implementing ML solutions.You are proficient in Python and have experience with ML/DL frameworks such as PyTorch, MetaFlow, or Jax.You excel at complex problem solving with innovative solutions, developing novel algorithms, and adapting existing methods from literature to new challenges. You are an excellent communicator, capable of explaining complex technical details to both technical and non-technical partners.You demonstrate Netflix values and bring new perspectives to continue improving our culture.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 to determine your compensation in the market range. The range for this role is $150,000 - $750,000.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.Job is open for no less than 7 days and will be removed when the position is filled.

Locations

  • USA (Remote)

Salary

150,000 - 750,000 USD / yearly

Estimated Salary Rangehigh confidence

350,000 - 550,000 USD / yearly

Source: ai estimated

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • proficiency in Pythonintermediate
  • experience with ML/DL frameworks such as PyTorch, MetaFlow, or Jaxintermediate
  • experience evaluating and monitoring machine learning systems in productionintermediate
  • understanding of feature engineering, data pipelines, and model lifecycle management ... using tools like Sparkintermediate
  • deploying ML systems at scale, particularly in distributed training environments and high-performance inferenceintermediate
  • complex problem solving with innovative solutions, developing novel algorithmsintermediate

Required Qualifications

  • You have a strong foundation in machine learning, including supervised and unsupervised learning, and deep learning architectures (e.g. recommendations, forecasting). (experience)
  • You have a track record of deploying ML systems at scale, particularly in distributed training environments and high-performance inference. (experience)
  • You have hands-on experience evaluating and monitoring machine learning systems in production. (experience)
  • You have a strong understanding of feature engineering, data pipelines, and model lifecycle management for large-scale data processing problems using tools like Spark. (experience)
  • You hold an advanced degree (MS or PhD) in Computer Science, Electrical Engineering, or a related technical field with a focus on machine learning or artificial intelligence. (degree in phd)
  • You have at least 5 years of relevant industry experience designing and implementing ML solutions. (experience, 5 years)
  • You are proficient in Python and have experience with ML/DL frameworks such as PyTorch, MetaFlow, or Jax. (experience)
  • You excel at complex problem solving with innovative solutions, developing novel algorithms, and adapting existing methods from literature to new challenges. (experience)
  • You are an excellent communicator, capable of explaining complex technical details to both technical and non-technical partners. (experience)
  • You demonstrate Netflix values and bring new perspectives to continue improving our culture. (experience)

Responsibilities

  • Own and innovate upon ML models that predict how members engage with our content slate and future launching titles, helping inform a range of decisions across the content, studio, and advertising domains.
  • Design, build, and deploy robust ML systems which scale to handle Netflix-sized data.
  • Automate ML workflows for training, tuning, and deployment; enabling faster experimentation and productization.
  • Optimize model performance and inference efficiency, ensuring scalability in high-throughput distributed environments.
  • Improve ML observability, model evaluations, model monitoring, and debugging tools to ensure reliability of deployed models.
  • Collaborate with scientists, data engineers, and infrastructure teams to define project roadmaps, ensure alignment of goals, and drive integration with downstream applications.
  • Transform research prototypes into high-quality production code, ensuring systems are maintainable, scalable, and performant.
  • Stay up to date with ML infrastructure advancements, identifying new technologies and best practices to enhance efficiency.

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https://explore.jobs.netflix.net/careers/job/790312289381?microsite=netflix.com

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