Growth Operations Lead – Field & Participant Quality

Instawork
Bengaluru, Karnataka, IndiaPosted 14 March 2026

Tech Stack

Job Description

Instawork is on a mission to create meaningful economic opportunities for skilled hourly professionals in communities around the globe. Our AI-powered labor marketplace helps local businesses scale, and enables global technology companies to push the frontiers of robotics and AI. Backed by world-class investors like Benchmark, Spark Capital, Craft Ventures, Greylock, Y Combinator, and others, we’re looking for exceptional talent to reimagine the way the world works. Overview We are building large-scale real-world systems used to train next-generation AI and robotics models. Our programs involve participants performing natural daily activities while recording egocentric data using specialized hardware. As we scale to more complex setups such as multi-camera rigs, we are looking for an operator who can bridge the gap between HR recruiting, field operations, vendor teams, and data insights to ensure we recruit the right participants and maintain strong data quality and diversity. Role Summary This role sits at the intersection of recruiting, operations, and data. The person will work closely with HR, field teams, and vendor partners (such as BPOs) to ensure we bring in the right participants, maintain operational discipline, and continuously improve the quality and diversity of the dataset. Key Responsibilities Participant Growth Recruitment Work with HR to define the right participant profiles for programs Ensure diversity across environments, households, and demographics Identify gaps in participant types and improve sourcing strategies Operations Quality Improvement Analyze operational data and identify patterns in participant behavior Detect issues such as repetitive tasks, staged recordings, or poor data quality Translate insights into improvements in recruitment, onboarding, and field operations Vendor Partner Management Manage external vendor partners such as BPO teams and field partners Ensure vendors follow operational guidelines and quality standards Coordinate onboarding, training, and performance tracking for vendor teams Field Program Optimization Work closely with field captains and operations teams to improve participant performance Design simple playbooks and training guidelines to improve task diversity and recording quality Run operational experiments to improve outcomes and scale programs efficiently Cross-Team Coordination Act as the bridge between HR, operations, vendor teams, and internal data teams Ensure operational decisions align with dataset needs and quality goals Ideal Candidate Profile 2–5 years of experience in operations, program management, marketplace operations, field operations, community operations, or vendor management Experience working with external partners, vendors, or BPO teams Strong people skills and ability to work closely with field teams and participants Comfort working with operational data and identifying patterns or issues Highly proactive and comfortable working in fast-moving environments Nice to Have Experience in marketplace or gig platforms (Uber, Swiggy, Zepto, Zomato, etc.) Experience managing field teams or distributed operations Experience working with research operations, surveys, or data collection programs Leadership experience in college such as running clubs, events, or student communities What Success Looks Like Recruit the right participants instead of just increasing numbers Maintain high quality and diversity in collected data Improve operational efficiency across vendors and field teams Detect and solve data quality issues early as programs scale Our Values Empathy, Trust Candor We put ourselves in the shoes of our colleagues and customers and don’t shy away from uncomfortable conversations, instead building trust through honest and direct feedback. Bias for Action We practice high-velocity decision-making, clear-eyed that we often operate with incomplete information. Growing quickly means it’s OK to be wrong, so long as we l ... (truncated, view full listing at source)
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