Machine Learning Engineer (L5) - Content & Media ML Foundations

Netflix

One of the world's leading entertainment services with 283 million paid memberships in over 190 countries enjoying TV series, films and games.

$150,000 - $750,000

Machine Learning

Staff Software Engineer

Remote

5+ years of experience

AI · Entertainment

Description For Machine Learning Engineer (L5) - Content & Media ML Foundations

Netflix, a global entertainment powerhouse with 283 million subscribers, is seeking a Staff Machine Learning Engineer for their Content & Media ML Foundations team. This role sits at the intersection of entertainment and cutting-edge AI technology, focusing on building foundational ML solutions that drive impact across content creation, promotion, member personalization, and advertising.

The position offers an opportunity to work with Netflix's unique media data, advancing multi-modal content understanding and exploring generative models for innovations in filmmaking and media intelligence. The role involves designing and optimizing ML pipelines, deploying large-scale models, and collaborating with scientists and engineers to integrate multimodal solutions into production systems.

Ideal candidates should bring at least 5 years of industry experience, with an advanced degree in Computer Science or related fields. Strong expertise in Python, deep learning frameworks, and a proven track record of deploying ML systems at scale are essential. The role demands both technical excellence and strong communication skills, as you'll be working with both technical and non-technical stakeholders.

Netflix offers a competitive compensation package ranging from $150,000 to $750,000, with the flexibility to choose between salary and stock options. The company provides comprehensive benefits including health plans, mental health support, 401(k) with employer match, and generous time-off policies. As a remote position, this role offers the freedom to work from anywhere in the USA while contributing to groundbreaking developments in content intelligence and machine learning at one of the world's most innovative entertainment companies.

Last updated a month ago

Responsibilities For Machine Learning Engineer (L5) - Content & Media ML Foundations

Design, build and optimize ML pipelines for content understanding and media intelligence
Develop and deploy large-scale ML models efficiently using Netflix's ML infrastructure
Optimize model performance and inference efficiency for scalability in high-throughput distributed environments
Automate ML workflows for training, tuning and deployment
Collaborate with ML scientists and engineers to integrate multimodal models
Improve ML observability, model evaluations, model monitoring, and debugging tools

Requirements For Machine Learning Engineer (L5) - Content & Media ML Foundations

Python

Strong foundation in machine learning and deep learning
Track record of deploying ML systems at scale
Hands-on experience with training large generative models
Strong understanding of feature engineering and data pipelines
Advanced degree (MS or PhD) in Computer Science, Electrical Engineering, or related field
At least 5 years of relevant industry experience
Proficient in Python and experience with ML/DL frameworks like PyTorch or Jax
Excellence in complex problem solving
Excellent communication skills
Ability to thrive in fast-paced dynamic environments

Benefits For Machine Learning Engineer (L5) - Content & Media ML Foundations

401k

Medical Insurance

Dental Insurance

Vision Insurance

Mental Health Assistance

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
Paid leave of absence programs
35 days annually for paid time off (hourly employees)
Flexible time off (salaried employees)

Netflix

One of the world's leading entertainment services with 283 million paid memberships in over 190 countries enjoying TV series, films and games.

$150,000 - $750,000

Machine Learning

Staff Software Engineer

Remote

5+ years of experience

AI · Entertainment

Netflix

Write a function to validate a string as a valid integer representation, handling signs and spaces.

Data Structures & AlgorithmsHard

Write a function that validates if a given string is a valid representation of an integer. The function should handle positive, negative, and zero values. It should also account for leading/trailing spaces, but return false if there are any non-numeric characters other than a single leading '+' or '-' sign. Details: The input is a string. The output is a boolean: true if the string represents a valid integer, false otherwise. A valid integer string can start with an optional '+' or '-' sign. The rest of the string must contain only digits. Leading and trailing whitespace should be ignored. The string must not contain any other non-numeric characters. Examples: +123 should return true -456 should return true 0 should return true +007 should return true abc should return false 12.3 should return false 1a should return false should return false ++12 should return false --12 should return false 12+ should return false 12- should return false Considerations: Handle empty strings gracefully. Be mindful of potential integer overflow issues (although the function does not need to explicitly check for it). Focus on validating the format of the string. Ensure your solution efficiently handles various edge cases and invalid inputs. Your function should demonstrate clear, concise, and well-documented code.

Strings

Netflix

How would you test a system made up of multiple sub systems?

System DesignEasy

Let's say you have a complex e-commerce system composed of several subsystems: a user authentication service, a product catalog, a shopping cart, an order processing module, and a payment gateway. Each of these subsystems interacts with others to provide the complete shopping experience. How would you approach testing this entire system to ensure it functions correctly, is reliable, and meets performance expectations? Please describe the types of tests you would perform, the tools you might use, and how you would handle potential challenges like coordinating testing across multiple teams or simulating real-world user traffic.

Arrays

Strings

Two Pointers

Stacks

Binary Search

Sliding Windows

Linked Lists

Trees

Recursion

Graphs

Dynamic Programming

Greedy Algorithms

Bit Manipulation

Database Problems

Netflix

Challenges with Java and Scala?

Behavioral

Could you elaborate on some challenges you've encountered while working with Java and Scala?

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