Operations Program Manager – Data Infrastructure - India

Company Overview

At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.

Position Overview

We are looking for a Operations Program Manager – Data Infrastructure to design and scale operational processes that power our robotics foundation model development. In this role, you will build the operational backbone across our data collection warehouses, annotation workflows, and office infrastructure — bringing rigor, systems thinking, and a high-ownership mindset to everything you touch..

Responsibilities

• Build and standardize scalable operational processes across data collection sites, warehouses, and annotation workflows
• Drive process excellence initiatives focused on quality, efficiency, throughput, and operational reliability
• Design SOPs, QA systems, metrics frameworks, escalation protocols, and operational dashboards
• Partner cross-functionally with operations, infrastructure, research, and vendor teams to operationalize large-scale data programs

Preferred Qualifications

• 4–5 years of experience in process engineering, program management, or operations excellence
• Strong foundation in Six Sigma, Lean methodologies, and operational optimization
• Background in automotive, manufacturing, supply chain, or other process-intensive industries
• High ownership mindset with strong analytical and execution capabilities

Base Salary Range

₹25—₹35 INR