Cantina logo

Senior Machine Learning Engineer, Post-Training

Cantina

About Cantina

Cantina is a pioneering social platform with the most advanced AI character creator. Our platform allows users to build, share, and interact with AI bots and friends directly in the Cantina or across the internet. Cantina bots are lifelike, social creatures capable of interacting wherever humans go online. Whether you want to recreate yourself using powerful AI, imagine someone new, or choose from thousands of existing characters, Cantina offers a new media type that provides creators with infinitely scalable and personalized content experiences combined with seamless group chat across voice, video, and text.

About The Role

As a Senior Machine Learning Engineer, Post-Training, you will be part of the team responsible for developing our powerful pretrained language models into intelligent, engaging, and aligned products. You will work across teams and our technical stack to improve our model performance and training methods, including data, compute, and algorithms. This role will allow you to shape the conversational experience of humans and bots.

Responsibilities

  • Run evaluation and analysis of pre-trained models against certain performance and alignment issues.
  • Address these issues with additional training and fine-tuning techniques like DPO or RLHF.
  • Create datasets to address these issues.
  • Develop algorithms to improve performance metrics.
  • Contribute to Cantina’s open-source ML projects.

Requirements

  • 5+ years of experience building production-grade LLMs or Speech & Audio machine learning models in industry and/or academic research settings.
  • Experience with data processing, analysis, and curation.
  • Strong understanding of modern machine learning techniques (DPO, RLHF, transformers, etc).
  • Track record of exceptional research or creative applied ML projects.
  • Experience with product experimentation and A/B testing.
  • Experience training large models in a distributed setting.
  • Familiarity with ML deployment and orchestration (Kubernetes, Docker, cloud).

Location

We have offices located in Sunnyvale, CA, San Francisco, CA, and Brooklyn, NY. While we have a strong focus on individuals near our office hubs, we offer fully remote and hybrid employment opportunities.

Pay Equity

In compliance with Pay Transparency Laws, the base salary range for this role is between $175,000 - $250,000 for those located in the San Francisco Bay Area, New York City, and Seattle, WA. When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.

Application Process

Please submit your resume, cover letter, and any relevant portfolio or publications demonstrating your research contributions in AI.

Benefits Summary

  • Health Care — 99% of premiums for medical, vision, dental are fully paid for by Cantina, plus One Medical membership.
  • Monthly Stipend — $500/month to use on whatever you’d like!
  • Rest and Recharge — 15 PTO days per year, 9 sick days, 13 paid company holidays, and offices closed for winter break (Christmas Eve to New Years Day)!
  • 401(K) — Eligible to participate on day one of employment.
  • Parental Leave & Fertility Support
  • Competitive Salary & Equity
  • Lunch and snacks provided for in-office employees.
  • WFH equipment provided for full-time hybrid/remote employees.

Benefits
Extracted with AI

  • Health Care — 99% of premiums for medical, vision, dental are fully paid for by Cantina, plus One Medical membership.
  • Monthly Stipend — $500/month to use on whatever you’d like!
  • Rest and Recharge — 15 PTO days per year, 9 sick days, 13 paid company holidays, and offices closed for winter break (Christmas Eve to New Years Day)!
  • 401(K) — Eligible to participate on day one of employment.
  • Parental Leave & Fertility Support
  • Competitive Salary & Equity
  • Lunch and snacks provided for in-office employees.
  • WFH equipment provided for full-time hybrid/remote employees.

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