Netflix is one of the world’s leading entertainment services with 278 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 Role
Software Engineer L5 — Machine Learning Build, Productivity, and Reliability Tooling
Our team builds developer productivity tools to enable Netflix’s machine learning teams. We’re looking for a passionate and talented engineer to join our team of engineers, SREs, and ML researchers.
As part of the team, you will design, build, and maintain tools that are used by our machine learning researchers daily. You will be part of a larger research organization that is responsible for Netflix’s core applied machine learning, which powers our recommendations, personalization, and search algorithms (and many other areas). You will work closely alongside our ML researchers to identify frictions, and to design and build solutions to them.
To be successful in this role, you must have a strong software engineering background, a keen sense of software design, and experience operating large CI/CD systems.
If you are ready to make a difference at a company that matters, and if you want to work with machine learning, and developer tools, in a company that strongly believes in both, then we would love to talk to you.
Requirements:
4+ years of software engineering experience with a successful track record of delivering quality results
Strong software design and development skills (Scala, Java, C#, or C++).
Experience with large-scale data frameworks such as Spark, Hadoop, etc.
Experience with parallel and distributed computing
BS in Computer Science or related field
Preferred, but not required:
Experience operating and customizing Bazel, or similar distributed build systems (such as Buck, Pants, etc).
Significant contributions to open source projects
Experience with machine learning frameworks, such as TensorFlow, PyTorch, etc
Netflix's culture is an integral part of our success, and we approach diversity and inclusion seriously and thoughtfully. We are an equal opportunity employer and celebrate diversity, recognizing that bringing together different perspectives and backgrounds helps build stronger teams. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
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 $100,000 - $720,000.
Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.
Netflix has a unique culture and environment. Learn more here.
We are an equal-opportunity employer and celebrate diversity, recognizing that diversity of thought and background 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.
