
Job Description
About the role
We’re looking for scrappy and self-motivated people who have full-stack machine learning skills: collecting data, training state-of-the-art models, building evaluations, writing efficient inference algorithms, and iterating on user feedback.
In the day-to-day, you will be responsible for developing new multimodal capabilities end-to-end. This means you will need to wear a lot of hats across the full ML stack. You should be comfortable thinking about all parts of the problem, and ready to work on any and all components of it.
Responsibilities
- Determining the type of training data we need, finding where we can collect it, and writing distributed data gathering pipelines to ingest data
- Developing new model architectures that push the state-of-the-art in terms of quality, scale, and inference speed
- Creating new evaluations that capture different aspects of generative outputs
- Writing fast inference algorithms to serve these models at scale
- Working with product teams to integrate feedback mechanisms into the product, which we use to improve the model
Requirements
- "All Industry Levels": preferably 2+ years of industry experience working deep in the weeds on hard ML problems.
- Negative example: just stringing together a bunch of pre-existing components together. Need signal that this person can think critically about different parts of the pipline
- Have a deep understanding of the “whole stack” when it comes to designing, training, evaluating and deploying machine learning models, especially large language models.
- Collected a new giant dataset
- Published research papers
- Played a critical role in shipping a new ML product that required custom components
- Writing distributed ML infrastructure
- Have debugged and fixed hard-to-find bugs in ML models
- Have a track record of successfully owning projects from start to finish.
- Have experience with generative models for various modalities.
- Experience working with proven tools: ML frameworks (Tensorflow, PyTorch, Jax, …), data processing frameworks (Spark, Beam, …).
About Character.AI
Founded in 2021, Character is a leading AI company offering personalized experiences through customizable AI 'Characters.' As one of the most widely used AI platforms worldwide, Character enables users to interact with AI tailored to their unique needs and preferences.
Company Info.
Character.ai
Character.ai is a neural language model chatbot service that can generate human-like text responses and participate in contextual conversation. Constructed by previous developers of Google's LaMDA, Noam Shazeer, and Daniel De Freitas, the beta model was made available to use by the public in September 2022.
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Character.ai is currently hiring Research Engineer Jobs in Menlo Park, CA, USA; New York City, NY, USA with average base salary of $225,000 - $400,000 / Year.