Machine Learning Engineer, Memory

San Francisco

Cantina

A new social platform where you can create, share, and interact with Al bots live with friends.

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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: 

As an ML Engineer: Memory, you'll take on a high priority/visibility and largely unsolved problem: designing and implementing a scalable approach to personalizing LLM outputs based on a user’s past interactions. You will:

  • Develop a system for compacting, storing, and retrieving bots’ “memories” to enhance real-time LLM inference.

  • Train ML models to incorporate personalization signals using techniques like LoRA, Adapters, MoE, HyperNetworks, prompt tuning, etc.

  • Leverage industry/academic research to ensure that our technology reflects and advances the state of the art.

A bit about you:

  • 5+ years of experience building production-grade, distributed systems on AWS or a similar cloud platform.

  • Exceptional programming skills in Go (preferred), Rust, Python, C++, etc. with an emphasis on designing for reliability and scale.

  • Proficiency with deep learning and NLP frameworks like Scikit-learn, PyTorch, TensorFlow, etc.

  • Hands-on experience building pipelines that leverage the latest LLMs.

  • Strong teamwork skills, with the ability to communicate and collaborate effectively with both technical and non-technical team members.

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.

Benefits Summary:

  • Health Care —  99% of premiums for medical, vision, dental are fully paid for by Cantina, plus One Medical membership.

  • Monthly Wellness Stipend — $500/month to use on whatever you’d like! 

  • Rest and Recharge — 15 PTO days per year, 10 sick days, all Federal holidays, and 2 floating holidays.

  • 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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Tags: AWS Deep Learning Distributed Systems LLMs LoRA Machine Learning ML models NLP Pipelines Python PyTorch Research Rust Scikit-learn TensorFlow

Perks/benefits: Career development Competitive pay Equity / stock options Fertility benefits Gear Health care Medical leave Parental leave Wellness

Region: North America
Country: United States

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