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Machine Learning Engineer, Data

A bit about Cantina:

Cantina, founded by Sean Parker, is a new social platform with the most advanced AI character creator. Build, share, and interact with AI bots and your friends directly in the Cantina or across the internet.

Cantina bots are lifelike, social creatures, capable of interacting wherever humans go on the internet. Recreate yourself using powerful AI, imagine someone new, or choose from thousands of existing characters. Bots are a new media type that offer a way for creators to share infinitely scalable and personalized content experiences combined with seamless group chat across voice, video, and text.

If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future!

A bit about the role: 

The Machine Learning, Data team focuses on two key areas: large-scale data collection and refined dataset creation. The ideal candidate will expertly manage diverse data sources, build robust infrastructure for petabyte-scale data handling, and craft comprehensive training datasets through experimentation and evaluation. This role is central to our AI development process, requiring meticulous attention to detail and the ability to make impactful design decisions.

As a ML Engineer, you will:

  • Identify and collect data at scale for large language models

  • Design and implement robust infrastructure for efficient petabyte-scale data collection, processing and streaming.

  • Develop ETL tools for managing vast amounts of data

  • Develop innovative solutions for data-related issues in AI model training and implement rigorous data validation processes

  • Ensure data integrity and relevance throughout the pipeline

  • Contribute to Cantina’s open-source ML projects and associated communities

A bit about you:

  • 5+ years of data platform  engineering or relevant experience

  • Experience building large-scale data processing pipelines, with tools like PySpark, Beam, or Flink

  • Familiarity with Machine Learning and NLP and willingness to learn more on the job

  • Track record of adapting to new domains and a desire to use data to improve products

  • ML experience as an ML engineer, Data Scientist, or another similar role

  • Experience with cloud platforms like AWS or Azure, or tools such as Kubernetes and Terraform

  • Passionate about Conversational AI or large language models

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 $250,000 - $350,000 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.

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What We’re About At Cantina we’re more than coworkers; we’re a community. Many Cantinistas bring their hobbies and outside interests to work with them. What We Believe Cantina is all about its people. To come up with game-changing ideas for our c...

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Full-time, hybrid
DATE POSTED
July 31, 2024

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