VP of Research, Machine Learning

Engg; Singapore; On-site; SGD 180,000 - 280,000; Full time

Job summary

A1 is building a proactive smart assistant for everyday tasks. We seek a leader to own the research and intelligence direction of our system, defining how AI reasons, evaluates, and improves in a high-frequency product.

You will guide architecture choices, evaluation, and guardrails to deliver reliable, scalable AI across billions of interactions. You’ll collaborate with product and engineering teams to set a high technical bar, drive rigor, and shape a roadmap for powerful reasoning, planning,

Qualifications

• Extensive experience building or evolving ML systems used in production.
• Strong judgment around model behavior, failure modes, and long-horizon trade-offs.
• Builder mindset focused on real-world, reliable systems.
• Comfort with irreversible or high-impact decisions under uncertainty.
• Obsessive about evaluation, correctness, and long-term system behavior.

Responsibilities

• Set and evolve the research direction for A1’s core intelligence, including context representation, memory, reasoning, planning, and orchestration.
• Decide when to design new model architectures versus adapting frontier open-source or commercial models.
• Define evaluation frameworks that measure real-world usefulness, robustness, safety, and long-term behavior.
• Own alignment, safety, and guardrail strategy as a first-class product concern.
• Guide exploration of frontier techniques such as retrieval-augmented training, mixture-of-experts, distillation, multi-agent orchestration, and multimodal systems.
• Shape early product intelligence direction in close partnership with product and application engineering.
• Set the technical bar for research rigor, judgment, and taste across the organization.

Skills

ML systems

Production ML

Model evaluation

Reasoning & planning

Guardrail strategy

Tools

Python

PyTorch

JAX

GPU training

Job description

ABOUT A1

There are over 5 billion users using basic applications today such email, notes, tasks that are not AI-native. Our mission is to build a proactive smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows, with minimal prompting. Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior. Our objective is to help users complete tasks daily enjoyable with over ~90%* reduced time.

ROLE

You will own the research and intelligence direction of this system. Your role is to define how AI reasons, evaluates, and improves in a product used with high frequency.

WHAT YOU'LL DO

• Set and evolve the research direction for A1’s core intelligence, including context representation, memory, reasoning, planning, and orchestration.
• Decide when to design new model architectures versus adapting or leveraging frontier open-source or commercial models.
• Define evaluation frameworks that measure real-world usefulness, robustness, safety, and long-term behavior – not benchmark vanity.
• Own alignment, safety, and guardrail strategy as first-class product concerns.
• Guide exploration of frontier techniques such as:
  • retrieval-augmented training
  • mixture-of-experts
  • distillation
  • multi-agent orchestration
  • multimodal systems
• Shape early product intelligence direction in close partnership with product and application engineering.
• Set the technical bar for research rigor, judgment, and taste across the organization.

REQUIREMENTS

• Deep experience building or evolving real machine learning systems used in production.
• Strong technical judgment around model behavior, failure modes, and long-horizon trade-offs.
• A builder’s mindset: you care about systems that work in the real world, not just ideas.
• Comfortable making irreversible or high-impact decisions with incomplete information.
• Obsession with evaluation, correctness, and how systems behave over time.
• High ownership mentality — you operate as a founder, not a manager.
• If you are looking to focus primarily on publishing, incremental benchmarks, or managing a large research organization, this role will not be a fit.

TECH STACK

• Python - PyTorch / JAX - GPU-based training and inference system

HOW WE WORK

The best products today in the world were built by small, world class teams. We are a high talent density and hands‑on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product.

INTERVIEW PROCESS

If there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews. Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite. We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.