Software Engineer L4/L5, Training Platform, Machine Learning Platform

5 Months ago • All levels • Artificial Intelligence • $100,000 PA - $720,000 PA

Job Summary

Job Description

Netflix seeks a Software Engineer to build and operate a large-scale ML training platform. Must have experience in ML engineering on production systems, building and operating large-scale infrastructure for ML use cases, and cloud computing. Expertise in deep learning models and distributed training is preferred.
Must have:
  • ML engineering
  • Production systems
  • Large-scale infrastructure
  • Cloud computing
Good to have:
  • SageMaker
  • Distributed training
  • Generative AI
  • Foundation models
Perks:
  • Stock options
  • Flexible time off

Job Details

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

Machine Learning/Artificial Intelligence powers innovation in all areas of the business, from helping members choose the right title for them through personalization, to better understanding our audience and our content slate, to optimizing our payment processing and other revenue-focused initiatives. Building highly scalable and differentiated ML infrastructure is key to accelerating this innovation.

The Opportunity

We are looking for a driven Software Engineer to join the Training Platform team under our Machine Learning Platform (MLP) org. MLP’s charter is to maximize the business impact of all ML use cases at Netflix through highly reliable and flexible ML tooling and infrastructure that supports key product functions such as personalized recommendations, studio algorithms, virtual productions, growth intelligence, and content demand modeling among others.

In this role you will get to: 

  • Design and build the platform that powers large-scale machine learning model training, fine-tuning, model transformation and evaluations workflows and use cases from the entire company

  • Co-design and optimize the systems and models to scale up and increase the cost-effectiveness of machine learning model training

  • Design easy-to-use APIs and interfaces for experienced ML practitioners, as well as non-experts to easy access the training platform

Minimum Job Qualifications

  • Experience in ML engineering on production systems dealing with training or inference of deep learning models.

  • Proven track record of building and operating large-scale infrastructure for machine learning use cases

  • Experience with cloud computing providers, preferably AWS

  • Comfortable with ambiguity and working across multiple layers of the tech stack to execute on both 0-to-1 and 1-to-100 projects

  • Adopt and promote best practices in operations, including observability, logging, reporting, and on-call processes to ensure engineering excellence.

  • Excellent written and verbal communication skills

  • Comfortable working in a team with peers and partners distributed across (US) geographies & time zones.

Preferred Qualifications

  • Understand modern and real-world Machine Learning model development workflows and experience partnering closely with ML modeling engineers

  • Familiarity with cloud-based AI/ML services (e.g., SageMaker, Bedrock, Databricks, OpenAI, etc.)

  • Experience with large-scale distributed training and different parallelism techniques for scaling up training, such as FSDP and tensor/pipeline parallelism

  • Expertise in the area of Generative AI, specifically when it comes to training foundation models, fine tuning them, and distilling them to smaller models

What do we offer?

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 .

Netflix has a unique culture and environment.  Learn more .  


 

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.

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About The Company

Netflix is one of the world's leading entertainment services with over 247 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.

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