Scaling a Global AI Team for a $2.4B E-commerce Leader

​

What Was the Challenge?

The client had been hiring directly but faced a bottleneck due to an incredibly narrow local talent pool and a notoriously exacting interview process. With a very low pass-through rate, the search required a partner who could run a global executive search campaign to find the specific culture-fit and technical expertise required.

How Did I Approach This Search?

Working closely with the hiring team I built a globally focused headhunt strategy, targeting key tech hubs known for advanced ML research and production-grade systems. We expanded the search parameters beyond Sydney, targeting candidates in high-density ML markets. Given the client's high standards, we acted as a primary filter, ensuring only those with the capability to handle Reinforcement Learning and Multi-Task Learning architectures reached the final stages. We also managed the complexities of pitching the Australian opportunity to international talent, focusing on the company's hyper-growth trajectory and world-class benefits.

What Results Were Achieved?

The project resulted in three successful senior-level placements sourced from three different countries: one candidate from Australia tapping into the best of the local resident talent, one candidate from Germany sourced from Europe's leading engineering talent pool, and one candidate from China headhunted from a major global AI research hub.

Key Outcomes:

• 3 senior-level Applied Scientists placed

• Candidates sourced from 3 countries (Australia, Germany, China)

• Global headhunt strategy across key ML hubs

• Rigorous vetting for Reinforcement Learning & Multi-Task Learning expertise

​