Building ML teams across the US and Europe for a fast-growing social platform
How we helped ShareChat and Moj scale Recommender Systems, Search, Ads and ML Platform capability outside India.
Cubiq have been helping our team hire the ML talent we need to support our main products. Communication is very smooth and the processes well defined. I am very happy and would highly recommend them to anyone else.
Wenzhe Shi
Senior Director, Applied ML
ShareChat
ShareChat is India’s largest regional social media platform, with 300m+ users across ShareChat and Moj. Its AI-driven recommendation and content systems power large-scale discovery and engagement across diverse language audiences.
Industry
Social Media, Artificial Intelligence
Discipline(s)
Machine Learning, Recommender Systems, Search, Ads, ML Platform, MLOps, Leadership
Company Size at Partnership
≈1,300 Employees
Growth Stage at Partnership
Series F / Pre-IPO
Brief
ShareChat, India’s largest regional social platform, set out to strengthen its global AI capability to keep pace with rapid user growth across ShareChat and Moj. With core teams based in India, leadership were facing a shortage of senior AI and ML expertise locally, particularly in recommender systems, search, and ads ranking.
The brief was to identify and secure senior executives and technical leaders across Europe and the US who could operate remotely, establish best practice, and lay the groundwork for future team expansion. They briefed us on 10–20 key hires within the first 12 months.
Challenges
When we began working together, ShareChat was growing fast but struggling to access senior AI talent.
The expertise they needed in recommender systems, search and ads ranking was concentrated in Europe and the US, outside of their established market.
Building remote-first teams in regions where the company had little visibility was difficult, especially when competing against major tech firms. At the same time, hiring processes were still taking shape, with job definitions, interview structures and evaluation criteria needing to be built from scratch.
The challenge was to deliver senior, high-impact hires quickly, while helping ShareChat put the foundations in place for long-term, scalable global hiring.
Approach
- The partnership began by securing a Senior Director of AI. Securing this hire early gave the firm the senior oversight needed to structure teams and define its global talent strategy.
- We followed with the Director of AI and Tech Lead appointments, creating a leadership spine across Recommender Systems, Ads and ML Infrastructure.
- Once the leadership layer was in place, our focus shifted to execution teams — delivering a series of Principal, Staff and Senior Machine Learning Engineers across Europe and the US, alongside Decision Scientists specialising in ranking and monetisation.
- To sustain hiring pace, we standardised job specifications, interview flows and evaluation rubrics, reducing ambiguity and enabling faster, consistent decision-making across global time zones.
- We built candidate pipelines by mapping teams at top firms such as Meta, Twitter and Google, leveraging direct outreach and technical calibration calls to validate alignment before submission.
- Regular calibration with ShareChat’s AI leadership meant we could adjust scope as new needs emerged, whether in ML Ops, Ads ranking or data science.
- As the partnership matured, we helped refine ShareChat’s remote hiring model, advising on regional pay structures and long-term team distribution to support future scaling.
ShareChat is India’s largest regional social media platform, with 300m+ users across ShareChat and Moj. Its AI-driven recommendation and content systems power large-scale discovery and engagement across diverse language audiences.
Industry
Social Media, Artificial Intelligence
Discipline(s)
Machine Learning, Recommender Systems, Search, Ads, ML Platform, MLOps, Leadership
Company Size at Partnership
≈1,300 Employees
Growth Stage at Partnership
Series F / Pre-IPO
Brief
ShareChat, India’s largest regional social platform, set out to strengthen its global AI capability to keep pace with rapid user growth across ShareChat and Moj. With core teams based in India, leadership were facing a shortage of senior AI and ML expertise locally, particularly in recommender systems, search, and ads ranking.
The brief was to identify and secure senior executives and technical leaders across Europe and the US who could operate remotely, establish best practice, and lay the groundwork for future team expansion. They briefed us on 10–20 key hires within the first 12 months.
Challenges
When we began working together, ShareChat was growing fast but struggling to access senior AI talent.
The expertise they needed in recommender systems, search and ads ranking was concentrated in Europe and the US, outside of their established market.
Building remote-first teams in regions where the company had little visibility was difficult, especially when competing against major tech firms. At the same time, hiring processes were still taking shape, with job definitions, interview structures and evaluation criteria needing to be built from scratch.
The challenge was to deliver senior, high-impact hires quickly, while helping ShareChat put the foundations in place for long-term, scalable global hiring.
Approach
- The partnership began by securing a Senior Director of AI. Securing this hire early gave the firm the senior oversight needed to structure teams and define its global talent strategy.
- We followed with the Director of AI and Tech Lead appointments, creating a leadership spine across Recommender Systems, Ads and ML Infrastructure.
- Once the leadership layer was in place, our focus shifted to execution teams — delivering a series of Principal, Staff and Senior Machine Learning Engineers across Europe and the US, alongside Decision Scientists specialising in ranking and monetisation.
- To sustain hiring pace, we standardised job specifications, interview flows and evaluation rubrics, reducing ambiguity and enabling faster, consistent decision-making across global time zones.
- We built candidate pipelines by mapping teams at top firms such as Meta, Twitter and Google, leveraging direct outreach and technical calibration calls to validate alignment before submission.
- Regular calibration with ShareChat’s AI leadership meant we could adjust scope as new needs emerged, whether in ML Ops, Ads ranking or data science.
- As the partnership matured, we helped refine ShareChat’s remote hiring model, advising on regional pay structures and long-term team distribution to support future scaling.
Results and impact.
20 specialist hires in our first 12 months of partnership, including two director-level appointments.
Secured top talent from Meta, Twitter, Google and other major tech firms.
Improved interview-to-hire efficiency by improving candidate evaluation frameworks and tightening process controls.
Elevated the ShareChat brand to AI, ML and data science talent outside of India.