VP of AI Engineering

Job Title: VP of AI Engineering

Job Type: Full-time

Location: Remote

About Us:

micro1 builds the human data and evaluation infrastructure that powers modern AI systems. Our platform is used by frontier AI labs and Fortune 10 companies to source, assess, and deploy elite human expertise directly into model training, evaluation, and feedback loops.

We combine applied AI, large-scale human data, and rigorous evaluation frameworks to improve model performance in production. From our AI recruiter and intelligence platform to internal data quality and research tooling, micro1 turns expert human judgment into high-signal datasets, measurable outcomes, and continuously improving AI systems.

Job Summary

The VP of AI owns and leads the company’s AI engineering function end to end, with a strong focus on delivering high-quality, production-ready AI systems. This role combines strategic leadership with hands-on execution, driving the development, evaluation, and deployment of applied AI across core products and research initiatives.

In this role you will lead a globally distributed AI engineering team, establish standards for model quality and evaluation, and partner closely with the CEO to shape technical strategy, hiring, and execution in support of the company’s product roadmap.

What You'll Do

• Own AI engineering across micro1’s core products, including Zara (AI Recruiter), Rhea AI, and research-facing tooling.
• Evaluate, fine-tune, and build on top of foundation models; train non-LLM models from scratch where needed.
• Establish best practices for model evals, human data, and feedback loops.
• Lead and scale a high-performance, hands-on AI engineering team.
• Contribute directly to model development and backend systems when required.
• Set direction for new AI tools and products in close partnership with Product and Engineering.
• Report directly to the CEO and support customer conversations when needed.

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What We're Looking For

• Deep, hands-on AI/ML engineering experience in production.
• Strong experience training models from scratch and fine-tuning LLMs.
• Excellent understanding of evals, human-in-the-loop systems, and data quality.
• Proven technical leadership with a strong execution mindset.
• Comfortable operating in fast-moving, ambiguous environments.

Preferred

• AI research background from a top school or AI lab (applied, not pure research).
• Experience with RLHF or human-feedback-driven systems.
• SF-based (big plus).