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Posted 2 months ago
Requirements and responsibilities
About micro1
micro1 builds the human data and evaluation infrastructure powering 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 research and data-quality tooling, micro1 turns expert human judgment into high-signal datasets, measurable outcomes, and continuously improving AI systems.
Role Summary
The VP of AI Engineering owns micro1’s AI engineering function end to end, with a strong focus on building, evaluating, and deploying production-grade AI systems.
This role blends technical leadership with hands-on execution. You will lead a globally distributed AI engineering team, set standards for model quality and evaluation, and partner directly with the CEO to define technical strategy, hiring, and execution aligned with 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 when needed.
- Establish best practices for model evaluation, human-in-the-loop systems, and data quality.
- Lead, mentor, and scale a high-performing, hands-on AI engineering team.
- Contribute directly to model development and backend systems when required.
- Set technical direction for new AI tools and products in close collaboration with Product and Engineering.
- Report directly to the CEO and support customer and partner conversations as needed.
What We’re Looking For
- Deep, hands-on experience building and shipping AI/ML systems in production.
- Strong background training models from scratch and fine-tuning LLMs.
- Solid understanding of model evaluation, human feedback loops, and data quality at scale.
- Proven technical leadership with an execution-first mindset.
- Comfort operating in fast-moving, ambiguous environments.
Nice to Have
- Applied AI research background from a top school or AI lab.
- Experience with RLHF or other human-feedback-driven systems.
- Based in San Francisco (or able to work closely with SF-based leadership).
Optionally, you can add more information later (benefits, pre-screening questions, etc.)