Machine Learning Software Engineer L4/L5

Netflix is one of the world's leading entertainment services with 283 million paid memberships in over 190 countries enjoying TV series, films and games.
United States
$100,000 - $720,000
Machine Learning
Staff Software Engineer
Remote
5,000+ Employees
4+ years of experience
AI · Entertainment

Description For Machine Learning Software Engineer L4/L5

Netflix, a global entertainment leader with 283 million subscribers, is seeking a Machine Learning Software Engineer to join their Algorithms team. This role combines software engineering expertise with machine learning to enhance Netflix's personalization systems.

The position offers a unique opportunity to work on large-scale ML systems that directly impact millions of users worldwide. You'll be responsible for designing and implementing scalable solutions for machine learning algorithms that power the Netflix experience, working alongside researchers, product managers, and engineers to innovate and improve existing systems.

The role requires strong software engineering fundamentals with expertise in Python and other languages like Scala or Java, plus experience with distributed computing systems and data frameworks such as Spark or Flink. You'll be working on cutting-edge projects involving personalization, recommendation systems, and machine learning platforms.

What makes this role exceptional is the scale and impact of the work - your contributions will directly influence how millions of Netflix users discover and enjoy content. The company offers a competitive compensation package ($100,000 - $720,000) with the flexibility to choose between salary and stock options, comprehensive benefits, and a culture that values inclusion and innovation.

The position is remote-based in the USA, offering the flexibility of working from anywhere while being part of a team that's pushing the boundaries of machine learning applications in entertainment. Netflix's unique culture emphasizes freedom and responsibility, allowing you to make significant technical decisions and drive innovation in how people consume entertainment worldwide.

This is an ideal opportunity for an experienced software engineer with a passion for machine learning who wants to work on challenging problems at scale, with access to vast amounts of data and resources to make a real impact in the entertainment industry.

Last updated a day ago

Responsibilities For Machine Learning Software Engineer L4/L5

  • Design, develop, and scale solutions for machine learning algorithms
  • Work with machine learning researchers, product managers, and other engineers
  • Implement scalable, flexible, production-ready solutions for algorithms
  • Guide the team towards better software engineering practices
  • Create solutions used beyond the team
  • Drive vision, requirements, design, implementation, testing, and ownership of software components
  • Collaborate with applied researchers and data scientists

Requirements For Machine Learning Software Engineer L4/L5

Python
Java
Scala
  • A degree in Computer Science or a related field
  • 4+ years of full time software engineering experience with a bachelor's degree; or 2+ years of experience with a graduate degree
  • Excellent software design and development skills in Python along with Scala, Java, C++, or C#
  • Solid understanding of various software engineering best practices
  • Experience building web-scale parallel and distributed computing systems
  • Experience with large-scale data frameworks such as Spark or Flink
  • Excellent collaboration skills
  • Broad understanding of core machine learning concepts

Benefits For Machine Learning Software Engineer L4/L5

Medical Insurance
Mental Health Assistance
401k
Vision Insurance
Dental Insurance
Parental Leave
  • 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 annually for paid time off (hourly employees)
  • Flexible time off (salaried employees)

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