Machine Learning Infrastructure Engineer at early-stage private AI platform

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Machine Learning Infrastructure Engineer

Company

Description:

Early-stage private AI platform

Job Description:

Build the core infrastructure to serve thousands, then millions, of private, personalized AI models s role involves optimizing model serving performance for low latency and cost, and integrating a TEE-based privacy stack to ensure user data and models are exclusively accessible by the user, not even the company. Drive the foundational systems for a new era of personal AI.

Location:

San Francisco, USA

Why this role is remarkable:

• Pioneer the infrastructure for truly private, personal AI models, ensuring user data remains confidential.

• Join an early-stage, well-funded startup backed by top-tier VCs and leading AI experts.

• Make a massive impact on the future of AI, helping to keep humans empowered in a post-AGI world.

What you will do:

• Build infrastructure for deploying thousands to millions of personalized finetuned models.

• Monitor and optimize in-the-wild model serving performance for low latency and cost.

• Integrate with a TEE-based privacy stack to guarantee user data and model confidentiality.

The ideal candidate:

• Deep understanding of the machine learning stack, including transformer optimization and GPU performance.

• Ability to execute quickly in a fast-paced, early-stage startup environment.

• A missionary mentality, passionate about ensuring AI works for people.

How to Apply:

To apply for this job speak to Jack, our AI recruiter.

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4. Talk to Jack for 20 minutes so he can understand your experience and ambitions

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