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NetflixNE

Machine Learning Engineer (L4) - Production Science

Netflix is the world's leading streaming entertainment service with over 195 million paid memberships in over 190 countries enjoying TV series, documentaries and feature films across a wide variety of genres and languages.

Netflix

Employee count: 5000+

Salary: 150k-750k USD

United States only

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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.

The Production Science team is part of the Data and Insights organization at Netflix. The team builds machine learning and analytics solutions to augment financial and operational decisions in the Netflix studio, supporting workflows like content planning, budgeting, scheduling, and financial forecasting. We are looking for an ML Engineer to help us develop, optimize and deploy models that directly integrate with internal workflows.

Responsibilities

  • Design, maintain, automate, and optimize ML training pipelines and realtime model serving infrastructure.

  • Improve ML observability, model evaluations, model monitoring, and debugging tools to ensure reliability of deployed models.

  • Collaborate closely with ML scientists and engineering teams to integrate deployed models into studio applications.

  • Develop new ML solutions to extract information from studio artifacts like scripts, budgets, cost reports, and schedules.

  • Stay up to date with ML infrastructure advancements, identifying new technologies and best practices to enhance efficiency.

About You

  • You have a strong foundation in machine learning, including supervised and unsupervised learning, and model evaluation.

  • You have a track record of deploying performant and scalable data-intensive applications.

  • You have a strong understanding of feature engineering, data pipelines, and model lifecycle management.

  • You hold an advanced degree (MS or PhD) in Computer Science, Electrical Engineering, or a related technical field with a focus on machine learning, artificial intelligence or computer vision.

  • You are proficient in Python and have experience with ML frameworks such as PyTorch, 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 audiences.

  • You are highly collaborative and thrive in dynamic environments, contributing positively to the team and company 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 diversitybuilds 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.

About the job

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Job type

Full Time

Experience level

Mid-level

Salary

Salary: 150k-750k USD

Location requirements

Hiring timezones

United States +/- 0 hours

About Netflix

Learn more about Netflix and their company culture.

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Netflix is the world's leading streaming entertainment service with over 195 million paid memberships in over 190 countries enjoying TV series, documentaries and feature films across a wide variety of genres and languages. Members can watch as much as they want, anytime, anywhere, on any internet-connected screen. Members can play, pause and resume watching, all without commercials or commitments.

A great workplace combines exceptional colleagues and hard problems.

Freedom and Responsibility

Our core philosophy is people over process. Our culture has been instrumental to our success and has helped us attract and retain stunning colleagues, making work here more satisfying.

Internet entertainment. Global original content. Product personalization.

Our first original series debuted in 2013. Over the following decades, Internet TV will replace linear, and we hope to keep leading by offering an amazing entertainment experience.

Employee benefits

Learn about the employee benefits and perks provided at Netflix.

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Healthcare benefits

Medical, dental, and vision insurance.

Time Away

Our vacation policy is “take vacation” and we actually do. Frankly, we intermix work and personal time quite a bit. Time away works differently at Netflix.

Paid parental leave

We recognize that one of the most special events in an individual's life is the birth or adoption of a child. Our parental leave policy is: "take care of your baby and yourself." New parents generally take 4 - 8 months.

Work, Not Drive

When it comes to your work schedule, commuting doesn’t always sync up and rush hour can be stressful. Work, not drive partners with a rideshare service that provides you the flexibility and focus on work while you commute.

View Netflix's employee benefits
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Netflix

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Netflix hiring Machine Learning Engineer (L4) - Production Science • Remote (Work from Home) | Himalayas