VP of Research (Machine Learning)

About the role

A stealth AI startup, backed by one of Southeast Asia's leading technology companies, is building its global founding team. It is developing an AI-native communication platform that integrates AI directly into conversations so users can plan, organize, compare, research and complete tasks in one intelligent assistant. The company is looking for a VP of Research (Machine Learning) to define and lead the research direction behind its AI platform, working closely with product and engineering leadership to balance cutting-edge research with practical production impact.

Key responsibilities

• Define and evolve the research roadmap for the platform's core AI intelligence, including context representation, memory, reasoning, planning and orchestration.
• Evaluate whether to develop proprietary model architectures or leverage and adapt frontier open-source and commercial AI models.
• Design evaluation frameworks measuring real-world performance, robustness, safety and long-term system behaviour beyond traditional benchmarks.
• Lead the company's AI alignment, safety and guardrail strategy as part of product development.
• Drive research and experimentation in RAG, Mixture of Experts, model distillation, multi-agent orchestration and multimodal AI systems.
• Partner with product and engineering teams to define and execute the intelligence strategy, and set high standards for research quality, technical judgment and engineering excellence.

Required profile

• Extensive experience designing, building and deploying machine learning systems in production.
• Strong technical expertise in model behaviour, failure analysis, system evaluation and long-term AI performance.
• Proven ability to turn advanced research into reliable, production-ready AI solutions.
• Demonstrated experience making high-impact technical decisions in fast-moving, ambiguous environments.
• Deep understanding of AI evaluation, model robustness, safety and system reliability.
• Strong ownership mindset and passion for practical AI systems with real-world impact.

Required skills

• Preferred: Python, PyTorch and/or JAX.
• Preferred: GPU-based model training and inference systems.