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Cantina

Subscription-based platform for AI-driven social gaming

Machine Learning Engineer - Core Evaluations

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeRemote

About the Job

Requirements

  • Strong experience and intuition for designing metrics that capture model performance.
  • Strong experience 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 comparing evaluation results statistically and making decisions.
  • Very strong engineering and programming skills.
  • Experience training automatic speech recognition and text-to-speech models.
  • Experience on machine learning teams working on large-scale machine learning problems, including models exceeding 3 billion parameters and more than 1 million hours of data.

Responsibilities

  • Design model evaluation pipelines for models in development and production.
  • Design user studies for subjective model evaluations.
  • Convert requirements into measurable metrics.
  • Design and develop automated evaluation dashboards to view model performance and compare results.
  • Train new models to capture new and different evaluation metrics.
  • Communicate with the model team to help design better models based on evaluation results.
  • Communicate with the data team to help decide what type of data is necessary to improve model performance.
  • Communicate with the product manager to ensure product requirements are measured correctly.
  • Help grow the evaluation team as its founding member.
  • Lead the evaluation team in the future.

About the Company

Cantina

Subscription-based platform for AI-driven social gaming

Cantina is a private, invitation-only platform that blends social gaming with AI-driven bots. Members join a 24/7 virtual club where they can chat with bots, play games, and create AI art under a monthly subscription. Bots have distinct personalities and adapt to user inputs, delivering personalized interactions in a shared space. It differentiates itself by offering a private, customizable, AI-driven social experience for tech-savvy gamers, with a goal to grow a steady subscription-based service and attract brand partnerships.

Company size
51-200
Company stage
Series B
Total funding
$33.3M
Headquarters
San Francisco, CA
Founded
2014

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