Machine Learning Software Engineer (L5) - Content and Studio

Netflix

World's leading entertainment service with 283 million paid memberships in over 190 countries, offering TV series, films and games.

$360,000 - $920,000

Machine Learning

Staff Software Engineer

Remote

5,000+ Employees

5+ years of experience

AI · Entertainment

Description For Machine Learning Software Engineer (L5) - Content and Studio

Netflix, the global entertainment leader serving 283 million subscribers worldwide, is seeking a Machine Learning Software Engineer for their Globalization Data Science and Engineering team. This role combines algorithmic expertise with full-stack engineering to revolutionize Netflix's localization products.

As an Algorithm Full Stack Engineer, you'll be at the forefront of removing language barriers and enhancing member experience globally. The position involves developing cutting-edge algorithms and creating tooling prototypes that process large-scale media assets. You'll work alongside scientists, engineers, and product managers to deliver impactful solutions for Netflix's content localization needs.

The role demands expertise in full-stack engineering, including frontend, backend, and cloud infrastructure, combined with strong algorithmic knowledge. You'll be responsible for designing systems, developing prototypes, and establishing integration pathways for algorithms. The position offers competitive compensation ($360,000 - $920,000) with flexible stock options and comprehensive benefits.

This is an exceptional opportunity for someone passionate about applying machine learning to content localization at scale. You'll have the autonomy to drive innovation while working with cutting-edge technology in a culture that values inclusion and diversity. The role offers the flexibility of remote work while contributing to Netflix's mission of entertaining the world through superior content experiences regardless of language barriers.

Last updated 17 days ago

Responsibilities For Machine Learning Software Engineer (L5) - Content and Studio

Design and develop systems and solutions for developing algorithm tooling prototypes and enabling in-depth algorithm evaluation
Propose and facilitate paved paths for integration and productization of algorithms
Identify and execute opportunities to create leverage for scaling algorithm impact
Contribute to algorithm projects end-to-end across different domains
Cultivate strong relationships with cross-functional partners
Evangelize best practices on algorithm full stack engineering

Requirements For Machine Learning Software Engineer (L5) - Content and Studio

Python

Proven track record of delivering high-impact algorithm-driven software systems
High proficiency in full stack engineering
Familiarity with algorithms and pipelines for processing large-scale media assets
Excellent communication and collaboration skills
Passion for bridging algorithms with tooling and workflows
Comfortable with ambiguity and able to take ownership
Netflix culture resonance

Benefits For Machine Learning Software Engineer (L5) - Content and Studio

401k

Medical Insurance

Mental Health Assistance

Vision Insurance

Dental Insurance

Equity

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
35 days annual PTO for hourly employees
Flexible time off for salaried employees

Netflix

World's leading entertainment service with 283 million paid memberships in over 190 countries, offering TV series, films and games.

$360,000 - $920,000

Machine Learning

Staff Software Engineer

Remote

5,000+ Employees

5+ years of experience

AI · Entertainment

Netflix

How to run threads A, B, and C in a sequence?

Data Structures & AlgorithmsMedium

How can you execute threads A, B, and C in a specific sequence using multithreading?

Dynamic Programming

Greedy Algorithms

Netflix

How would you design a tool to evaluate GitHub repository popularity based on metrics like stars and forks, including features like data fetching, score calculation, and visualization, while addressing API rate limiting and customization?

System DesignEasy

Let's design a tool to evaluate GitHub repositories based on metrics like stars and forks. Functionality:** The tool should: Fetch data from the GitHub API (stars, forks, open issues, contributors, etc.) for a given repository. Calculate a popularity score based on a weighted combination of these metrics. For example, stars might have a higher weight than open issues. Allow users to compare multiple repositories side-by-side. Present the data in a clear and visual way (charts, graphs, tables). Allow users to customize the weights used in the popularity score calculation. Handle API rate limiting gracefully (e.g., caching, authentication). Include features for trending topics/repositories. Example:** A user wants to compare the popularity of facebook/react versus angular/angular. They should be able to enter these repositories into the tool and see a comparison table showing the number of stars, forks, open issues, and the calculated popularity score for each. The user should also be able to adjust the weight given to stars in the popularity score to see how it affects the overall ranking. Consider additional features like displaying the rate of growth over the last month/year. What are the key components, architecture, and considerations for building such a tool, and what technologies would you choose and why?

Graphs

Dynamic Programming

Greedy Algorithms

Netflix

Tell me about a time you went above and beyond in a project.

Behavioral

Tell me about a time you went above and beyond in a project. What was the situation, what actions did you take, and what was the result? For example, perhaps you identified a critical bug that wasn't in your assigned area and took the initiative to fix it, or maybe you proactively automated a manual process that saved the team significant time. Detail the specific steps you took and the impact your actions had on the project's success or the team's efficiency. What did you learn from that experience, and how has it influenced your approach to projects since then? Focus on demonstrating your problem-solving skills, your ability to anticipate needs, and your commitment to delivering exceptional results.

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