About Populix

Populix is ​​a research-driven growth consultancy that helps businesses, institutions, and government agencies gain a clearer understanding of consumers, stakeholders, and opportunities. By combining data, technology, and deep expertise, Populix helps clients identify what truly matters, transform insights into tangible actions, and measure their impact. Populix’s services cover the entire growth journey—ranging from market research and policy & public research to campaign strategy, execution, amplification, and performance measurement. Populix also offers PopSurvey, an online self-service survey platform that enables users to access insights more quickly and efficiently. To download the latest studies from Populix, please visit info.populix.co.

About the Role

Our mission is to simulate human behavior and attitude: building technology that can model how real people think, feel, and respond, grounded in real psychographic data (belief systems, personality, values, decision patterns, and more). This capability powers faster, cheaper, and more scalable ways for our clients to understand and predict human responses, across market research, product testing, and beyond.

We're expanding into Singapore as part of a forward-deployed go-to-market model, and are looking for someone who can build and ship prototypes fast, while also bringing deep technical understanding of how modern AI/generative models actually work, enough to push the underlying science forward, not just wire together APIs. This person will be based in Singapore and act as the initial forward-deployed lead: sitting directly with clients on the ground, understanding their needs, and shipping tailored simulation solutions as part of our Singapore foothold.

This is a founding role. You'll start hands-on, proving out the playbook for how this technology gets delivered to clients in Singapore. Once that playbook works, you'll be expected to hire and lead the team that scales it, growing from individual contributor into the lead of our Singapore practice.

What You'll Do

• Own the technical build of human simulation solutions end-to-end: from ingesting survey/interview data to producing validated models that can predict how a person would think, feel, or respond.
• Rapidly prototype and iterate on new modeling approaches, prompting/fine-tuning strategies, and evaluation methods.
• Work directly with enterprise clients to scope custom use cases, translate their research or business needs into a working deployment, and stay hands-on through delivery.
• Push forward the underlying research: behavioral fidelity, bias and failure modes, evaluation methodology (e.g., how well a simulated response distribution matches a real one), and how far these models can be extrapolated beyond the data they were built on.
• Partner closely with the core AI/Model team to keep custom, client-facing work connected to the broader platform.
• Once the delivery playbook is validated, hire, build, and lead the team that scales this work across Singapore.

What We're Looking For

• A builder first. You can go from idea to working prototype fast, and you're comfortable operating with MVP-level scrappiness in a startup environment.
• Deep LLM/ML expertise. PhD (or equivalent research depth) in Machine Learning, NLP, Computer Science, Cognitive Science, or a related field, with hands-on expertise in deep learning, LLMs, and ideally reinforcement learning.
• Research instincts. You understand the inner workings of LLMs well enough to reason about why a model fails, not just tune parameters until it looks better.
• Client-facing comfort. You're excited by (not drained by) sitting with clients, understanding messy real-world requirements, and shipping something custom and useful quickly.
• Strong communication skills. Able to explain technical trade-offs to non-technical stakeholders and clients.
• Founder's mindset. Comfortable starting solo and figuring things out with limited structure, with a genuine desire to eventually hire and lead a team once the model is proven.

Nice to Have

• Experience with agent-based simulation, generative/synthetic agents, or synthetic user research.
• Background in psychometrics, survey methodology, or consumer/market research.
• Publication record at top ML/NLP venues (e.g., NeurIPS, ACL, ICML, UIST).
• Prior experience in an early-stage startup or forward-deployed engineering role.