TLDRs
- Uber expands India engineering footprint with massive new campus plan
- Bengaluru and Hyderabad hubs to host 9,600 employees by 2027
- Company boosts AI, autonomy, and infrastructure hiring across India teams
- Uber partners with Adani to build first India data center project
Uber is making a major long-term bet on India’s role in global technology development, announcing plans to significantly expand its engineering footprint with two new large-scale campuses in Bengaluru and Hyderabad.
The ride-hailing and mobility giant said on May 14 that the facilities are expected to collectively host around 9,600 employees by the end of 2027, marking one of its most ambitious workforce expansions in the region to date.
The move highlights how Uber is increasingly shifting beyond its traditional ride-hailing business, strengthening its focus on artificial intelligence, machine learning, and advanced infrastructure development. India, already a critical hub for global tech talent, is now becoming a central pillar in Uber’s long-term engineering and AI strategy.
Massive India Expansion Plan
Uber currently employs roughly 3,500 people in India, but the new campuses will nearly triple that figure over the next few years. The expansion underscores the company’s growing reliance on Indian engineering talent to build core technologies that support its global platform.
The Bengaluru and Hyderabad hubs will not just scale headcount but are expected to become key centers for innovation. Uber has indicated that hiring will span multiple advanced technical domains, including AI research, backend infrastructure, machine learning systems, and autonomous vehicle operations.
AI and Talent Push Accelerates
A significant portion of the new roles will be focused on artificial intelligence and applied machine learning. Uber’s Applied AI teams work on generative AI systems and computer vision models that support both platform optimization and product development.
Another key focus is autonomous systems. In Hyderabad, teams are involved in human-in-the-loop (HITL) annotation work, which includes labeling complex datasets such as 2D and 3D LiDAR inputs used to train self-driving models. This type of work is critical for improving machine perception systems that power next-generation mobility solutions.
Uber has also been expanding its “Uber AI Solutions” division, which aims to build large-scale data infrastructure and advanced model training systems. The India expansion is expected to strengthen these capabilities further.
Data Center Partnership With Adani
Alongside its campus expansion, Uber also announced plans to build its first local data center in India in partnership with the Adani Group. The facility is expected to go live in the fourth quarter of 2026.
The collaboration signals a strategic shift in how global tech companies approach infrastructure in India. Rather than relying solely on global cloud providers, Uber is partnering with a major domestic conglomerate with expertise in energy, logistics, and large-scale infrastructure development.
Access to land, power, and regulatory alignment is a key advantage of the partnership. These factors are increasingly important as AI workloads require significantly higher computational capacity and localized data processing.
India’s Growing Strategic Role
India has become a major engineering and innovation base for global technology firms, and Uber’s expansion reinforces this trend. The company invested around $330 million into its India unit earlier in 2026 as it seeks to diversify beyond ride-hailing and strengthen its competitiveness against local players such as Rapido.
The broader context of Uber’s strategy suggests a deliberate pivot toward becoming an AI-first mobility and technology company, with India positioned as a central execution hub.
As global demand for AI infrastructure continues to grow, Uber’s dual investment in both talent and physical computing infrastructure signals a long-term commitment to scaling its technology capabilities from one of the world’s fastest-growing tech ecosystems.
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