Machine Learning Engineer, Core Evaluations

🕒 April 29

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Logo of Cantina

Cantina

51 - 200 employees

Founded founded by Sean Parker

🤖 Artificial Intelligence

🎮 Gaming

🌍 Social Impact

Artificial Intelligence • Gaming • Social Impact

Cantina is a company that specializes in creating advanced AI characters that can talk, feel, and capture their adventures with selfies. It offers a platform where users can unleash their AI bots in online communities, allowing these lifelike, social creatures to interact with humans. Cantina focuses on building networks of AI influencers and encourages users to explore and build their own collections of AI bots. The company's mission is to foster an interactive universe, inviting creativity and social interaction through digital personalities and AI technology.

📋 Description

• Designing model evaluation pipelines for models in development and production • Designing user studies for subjective model evaluations. • Converting requirements into measurable metrics. • Designing and developing automated evaluation dashboard to see model performances and compare results. • Training new models to capture new and different evaluation metrics. • Communicating with the model team to help design better models based on the evaluation results. • Communicating with the data team to help decide the type of data necessary to improve model performance. • Communication with the product-manager to make sure product requirements are correctly measured. • Help grow the evaluation team as the founding member. • Lead the evaluation team in the future.

🎯 Requirements

• Strong experience and intuition for designing metrics that capture model performance. • Strong experience with designing user studies on Mechanical Turk or similar platforms. • Strong experience with model training and fine-tuning for model evaluation. • Strong statistical knowledge and experience to statistically compare evaluation results and take decisions. • Very strong engineering and programming skills. • Experience with training ASR, TTS models. • Experience at ML teams working on large-scale machine learning problems. (>3B models with >1m hours of data)

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