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Head of Quality Assurance - Instawork Robotics Labs

Instawork · instawork.com
BengaluruDirector10+ yrs
Apply on Instawork’s site
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The job in short

Quality assurance leadership for robotics labs.

Machine learningComputer visionAuditSupply chain

Details

Found
36 d ago · posted 2026-08-31
Location
Bengaluru, Karnataka, IN

Full description

About IRL (Instawork Robotics Labs) Researchers at UC Berkeley have identified a “100,000-year data gap” - the gulf between what trained AI language models and what physical robots actually have to learn from. Closing that gap is the defining infrastructure challenge of the physical AI era. IRL is Instawork’s answer to it. We deploy skilled workers into real commercial and residential environments - kitchens, warehouses, hotel floors, homes - to capture the high-fidelity task data that the world’s leading Robotics labs use to train their foundation models. Read more here. Location: Bangalore Experience: 10+ years Industry: Automotive / Mobility / Robotics / Manufacturing About the Role Instawork Robotics creates the highest-quality, highest-diversity datasets for robotics and physical AI. We work with many of the most important robotics builders and research labs to solve the most important challenge in robotics - closing the data gap. We are looking for a Head of QA with 10+ years of experience in automotive, manufacturing, mobility, robotics, or a closely related industry. This person will own the end-to-end quality and data-labeling function across Quality Assurance, Quality Control, Visual Inspection, and process quality. This is a hands-on leadership role for someone who can build quality systems from the ground up, establish rigorous processes, lead teams, and drive a strong quality culture across operations and engineering. What You'll Do • Own the QA/QC function: Build and lead the overall quality strategy, processes, standards, and KPIs across operations and manufacturing. • Visual & Product Quality: Establish robust visual inspection and defect detection processes, including inspection standards, sampling methodologies, defect classification, and root-cause analysis. • Quality Systems: Design and implement SOPs, inspection protocols, quality gates, audit mechanisms, CAPA, and continuous improvement processes. • Team Leadership: Build, manage, and develop high-performing QA/QC teams across locations and functions. • Cross-functional Quality: Partner closely with Engineering, Operations, Manufacturing, Supply Chain, and Product teams to identify and eliminate recurring quality issues. • Data & Metrics: Build quality dashboards and drive metrics such as defect rates, first-pass yield, rework, rejection rates, customer complaints, and quality escapes. • Supplier & Process Quality: Drive supplier quality, incoming inspection, in-process quality, and final inspection standards. • Root Cause & Continuous Improvement: Lead RCA, corrective/preventive actions, and quality improvement initiatives using structured methodologies such as 8D, FMEA, SPC, Six Sigma, or similar frameworks. What We're Looking For • 10+ years of experience in QA/QC, preferably in the automotive, manufacturing, robotics, mobility, electronics, or hardware industry. • Strong experience setting up and scaling multi-layer quality functions and processes from the ground up. • Experience leading QA and data-labeling operations for Petabyte-scale pipelines of real-world data • Experience working closely with machine learning, computer vision, robotics, or AI researchers on high-quality AI training datasets. • Experience managing large or distributed QA/QC teams. • Strong knowledge of root-cause analysis, CAPA, FMEA, 8D, SPC, and quality management systems. • Strong analytical and problem-solving skills with a data-driven approach to quality. • Excellent stakeholder management and communication skills. • A hands-on, high-ownership mindset — someone who is comfortable being on the floor, solving problems, and building processes rather than just managing them. Good to Have • Experience with automotive quality standards such as IATF 16949. • Exposure to computer vision, automated inspection, AI-based visual QA, or robotics. • Experience in a fast-scaling startup or high-growth manufacturing environment. • Six Sigma / Quality certification.

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