Machine Learning Researcher

4 days ago


Los Angeles, California, United States Netflix Full time
Unlock the Future of Entertainment with Netflix

At Netflix, we're revolutionizing the way people enjoy entertainment. As a Machine Learning Research Intern, you'll be part of a team that's pushing the boundaries of what's possible with AI and machine learning. Our research spans multiple areas, including recommender systems, natural language processing, computer vision, and more.

What You'll Do
  • Contribute to the development of cutting-edge machine learning models and algorithms
  • Collaborate with our research team to explore new ideas and applications
  • Work on real-world projects that impact our business and customer experience
What We're Looking For
  • Currently enrolled PhD or MS student in the Machine Learning space, or PhD graduate seeking postdoctoral research
  • Experience with at least one of the following ML areas: personalization & recommender systems, natural language processing, computer vision, reinforcement learning, or multimodal data
  • Strong programming skills in languages like Python or C/C++
  • Experience developing ML models using common frameworks like PyTorch, TensorFlow, or Keras
Why Netflix?

We're a company that values diversity, equity, and inclusion. We believe that a diverse team is a stronger team, and we're committed to creating an environment where everyone can thrive. Our internship program is designed to provide a personalized experience, with opportunities to work on real-world projects and collaborate with our research team.

We offer a competitive compensation package, with a market range of $40/hour - $110/hour. Our internship program is typically 12 weeks, with a choice of start dates in September or October. Conditions permitting, the internship will be located in our Los Gatos, CA office or Los Angeles, CA office.

We're an equal-opportunity employer, and we celebrate diversity in all its forms. We're committed to creating an inclusive environment where everyone can contribute their best work.



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