Machine Learning Researcher at Astera Institute focusing on data - efficient and general model induction. Collaborating on innovative architectures with a focus on performance and throughput.
About the role
- Machine Learning/AI Scientist Intern contributing to various machine learning areas for Netflix's research. Collaborating with teams on algorithms, tools, and optimizations.
Responsibilities
- Machine Learning Research at Netflix improves various aspects of our business, including personalization algorithms, member and title understanding, creative tooling, system optimization, and innovative tooling
- Collaborate with teams across organizations including Content, Choosing & Conversation, Commerce or AI for Member Systems
- Implementing machine learning solutions across various domains, end-to-end ML pipelines, from experimentation to deployment
Requirements
- Currently enrolled student pursuing an advanced degree (PhD) in areas such as Computer Science, Machine Learning, Artificial Intelligence, Computer Engineering, Mathematics, Statistics, Data Science, Economics, Computational Biology, Chemistry, Physics, Cognitive Science or a related field
- Domain expertise in one or more of the following areas: Personalization & Recommender Systems, Natural Language Processing, Reinforcement Learning, Computer Vision, Computer Graphics, Reliable ML, Causal ML, Agentic AI, Multimodal Data, Model Optimization and Efficiency, ML Platform & Infrastructure, General ML Application Engineering
- Experience programming in at least one programming language (Python, Java, Scala, or C/C++)
- Familiarity developing ML models using common frameworks (e.g., PyTorch, TensorFlow, Keras)
- Familiarity with distributed training and inference paradigms and associated frameworks (eg. DDP, FSDP, HSDP, Deepspeed)
- Familiarity with end-to-end machine learning pipelines (e.g. training or production deployment) and common challenges like explainability
- Curious, self-motivated, and excited about solving open-ended challenges at Netflix
Benefits
- Internships are paid
- Flexible working hours
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