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Company | Magic |
Address | San Francisco Bay Area, United States |
Employment type | FULL_TIME |
Salary | |
Expires | 2023-05-16 |
Posted at | 1 year ago |
Join us to build and safely deploy aligned, superhuman AI. For decades, technology was "just a tool" - could it be a colleague?
For decades, technology was “just a tool.” Soon, it will be a partner. We are building an AI pair programmer that feels like a full colleague inside your computer - capable, conversational, and reliable across domains. If this isn't AGI, then what is? Join us if you want to build and safely deploy aligned AGI in products that matter.
As a Research Engineer, you’ll work on training, evaluating, and serving large AI models, internet-scale dataset building, and help prototype new research and product ideas.
Work you might work on
Pre-training: Distributed training across large GPU clusters
Inference: Optimizing inference throughput of a custom neural net architecture
RL: Continual learning to train AI models on user feedback
Tool use: Implement interfaces to allow our AI models to interact with real-world tools or APIs
Algorithms: Designing, testing, and optimizing new neural net architectures
Internet-scale data: E.g. scraping much of YouTube
For decades, technology was “just a tool.” Soon, it will be a partner. We are building an AI pair programmer that feels like a full colleague inside your computer - capable, conversational, and reliable across domains. If this isn't AGI, then what is? Join us if you want to build and safely deploy aligned AGI in products that matter.
As a Research Engineer, you’ll work on training, evaluating, and serving large AI models, internet-scale dataset building, and help prototype new research and product ideas.
Work you might work on
Pre-training: Distributed training across large GPU clusters
Inference: Optimizing inference throughput of a custom neural net architecture
RL: Continual learning to train AI models on user feedback
Tool use: Implement interfaces to allow our AI models to interact with real-world tools or APIs
Algorithms: Designing, testing, and optimizing new neural net architectures
Internet-scale data: E.g. scraping much of YouTube
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