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Netflix

Software Engineer (L5) - ML - Studio & Creative Production Data Engineering

Posted 15 Days Ago
In-Office
Los Angeles, CA
170K-720K Annually
Mid level
In-Office
Los Angeles, CA
170K-720K Annually
Mid level
Design and build end-to-end tools and datasets for training and fine-tuning multi-modal generative models (video-focused). Implement large-scale batch inference and media data pipelines, contribute to storage/cataloging tooling, and partner with researchers, engineers, and product teams to operationalize Media ML at scale.
The summary above was generated by AI

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 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.

Netflix is revolutionizing the entertainment industry with world-class technology. We serve 300+ million members across 190+ countries, delivering billions of hours of great movies & TV shows every month in 30+ languages. To meet our members’ entertainment needs, Netflix has invested in scaled Content Production & Promotion workflows. With assistance from creative supervision and member feedback data, we have built tools & processes that use technologies like Computer Vision, Graphics, Machine Learning & Generative methods to enable our creators to tell the best version of the story they want while allowing our studio to scale further.

The Content Production & Promotion Data Engineering team, within Data Science and Engineering, is responsible for enabling our partners to develop data-driven workflow tooling that shapes the future of content production and promotion at a global scale. In collaboration with our partners, we unlock hidden insights and enable capabilities by implementing AI and Machine Learning techniques on voluminous and novel datasets (including media like artwork and video) and expose resultant datasets via user friendly API’s that hide the underlying complexity. 

We are looking for an experienced Machine Learning Software Engineer with a background in Computer Vision to help us build and ship AI workloads at scale.

What will you do?

  • Work alongside researchers, engineers, data scientists, and product managers in designing and building custom datasets for the purpose of training and fine-tuning generative models in a multi-modality fashion with a focus on video.

  • Develop end-to-end frameworks and tools to generate said datasets by leveraging the optimal resources needed to achieve the best possible performance at a reasonable cost.

  • Contribute to broader tooling initiatives that aid in the storage, cataloging, discovery and overall management of ML media.

  • Serve as a key thought partner for stakeholders, cross-functional partners, and our diverse set of team members regarding large/novel datasets in order to drive incremental value to our Media ML system architecture.

  • Engage with the Data Engineering and ML community, internal and external, to learn, to teach, and to contribute to building a great Netflix brand.

About you

  • Beyond talented, you are curious, creative, and tenacious.

  • You are not bothered by ambiguity, you find joy in finding patterns in the most complex of environments and bringing order into chaos.

  • You have a strong foundation in distributed system architecture (with excellent judgment on specific components such as GPU/CPU) and experience in large-scale batch inference and data processing.

  • Excellent software design and development skills in Python. Experience with SQL along with Scala or Java desired.

  • Experience with preparing and normalizing media data for Machine Learning workloads using libraries such as OpenCV, FFMpeg, Pytorch, HugginFace.

  • You are an excellent communicator, capable of explaining complex technical details to both technical and non-technical audiences.

  • 4+ years of full-time work experience in one or more relevant ML/SWE/Data Engineering roles.

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 $170,000 - $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 detail about our Benefits here.

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 diversity 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.

HQ

Netflix Los Gatos, California, USA Office

100 Winchester Circle, Los Gatos, CA, United States

Netflix San Jose, California, USA Office

San Jose, United States, 0

Netflix Santa Clara, California, USA Office

Santa Clara, United States, 0

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