Technical Lead Manager, Model Quality (AI)

TL;DR

Technical Lead Manager, Model Quality (AI): Building and leading the Model Quality engineering team, focusing on eval systems, data pipelines, and experimentation infrastructure. Focus on translating open research questions into engineering priorities and ensuring capability improvements show up in the product.

Location: Hybrid, must be in San Francisco, CA or New York City, NY at least 25% of the time.

Salary: $1 - $2 USD

Company

hirify.global’s mission is to create reliable, interpretable, and steerable AI systems.

What you will do

• Own the technical roadmap for model quality infrastructure on Claude Code, including eval frameworks, experimentation tooling, and data pipelines.
• Be accountable for the reliability and correctness of systems that researchers depend on daily.
• Hire and support a team of engineers.
• Partner closely with research leadership to translate open questions into engineering priorities.
• Collaborate with Claude Code product to ensure capability improvements are reflected in the product.
• Stay close to the code.

Requirements

• Have led engineering teams (as a manager or tech lead) building complex infrastructure such as data platforms, ML tooling, eval systems, or research computing.
• Be a strong IC engineer and want to stay technical.
• Have operated in high-intensity, fast-iteration environments and know how to keep a team moving without burning out.
• Comfortable navigating ambiguity across organizational boundaries and aligning teams with different incentives on shared goals.
• Be a power user of agentic coding tools and have real intuition for where models are strong and where they break.
• Care deeply about correctness and reliability, and can instill that bar in a team.
• Have 8+ years of engineering experience, including 2+ leading teams.
• Must have at least a Bachelor's degree in a related field or equivalent experience.

Nice to have

• Built or maintained evaluation frameworks for ML systems.
• Experience with reinforcement learning infrastructure.
• A background in research computing, scientific infrastructure, or ranking and recommendation systems.
• Experience with production ML monitoring and observability.
• A strong quantitative foundation.

Culture & Benefits

• Competitive compensation and benefits.
• Optional equity donation matching.
• Generous vacation and parental leave.
• Flexible working hours.
• Lovely office space in which to collaborate with colleagues.

Hiring process

• hirify.global recruiters only contact you from @hirify.global.com email addresses.
• Be cautious of emails from other domains.
• Legitimate hirify.global recruiters will never ask for money, fees, or banking information before your first day.