VP of Research, Machine Learning (AI)

TL;DR

VP of Research, Machine Learning (AI): Defining research and intelligence direction for a proactive AI chat application with an accent on persistent context, multi-step reasoning, and real-world task completion. Focus on building robust evaluation frameworks, architecting memory systems, and ensuring reliable model behavior in production environments.

Location: Must be based in Beijing, China (Remote)

Company

hirify.global is building a high-reliability, proactive AI conversational assistant designed to manage complex workflows and persistent user context.

What you will do

• Set and evolve the research strategy for core intelligence, including memory, reasoning, planning, and orchestration.
• Define and implement evaluation frameworks that measure real-world usefulness, safety, and long-term system robustness.
• Decide when to design custom model architectures versus adapting existing frontier models.
• Guide the exploration of advanced techniques such as mixture-of-experts, retrieval-augmented training, and multimodal systems.
• Establish the technical bar for research rigor and judgment across the organization.
• Partner closely with product and engineering teams to shape early product intelligence directions.

Requirements

• Must be based in Beijing, China
• Deep experience building or evolving real-world machine learning systems in production environments.
• Strong technical judgment regarding model behavior, failure modes, and architectural trade-offs.
• A builder's mindset with a focus on delivering functional systems rather than incremental research benchmarks.
• Ability to make high-impact decisions with incomplete information.
• High ownership mentality and experience operating with a founder-level approach.

Culture & Benefits

• High talent density, hands-on, world-class engineering environment.
• Decisions made collectively at rapid speed with a focus on shipping quality work.
• Emphasis on transparency, efficiency, and independent execution.
• Direct contribution to a product aiming to bring practical AI benefits to a global audience.

Hiring process

• Evaluation of applications by the technical team.
• 3 to 4 virtual or onsite interviews.
• Focus on transparency with prompt decision-making.