Data Quality Team Lead at Instrumental, Inc. – Palo Alto, California

Instrumental technology is used by the world’s most admired electronics brands, such as NVIDIA, Cisco, and Meta, to accelerate new product development and improve production yields. Our technology leverages AI to process data generated on the manufacturing floor, automating failure identification and resolution, improving yield, quality, and time-to-market. In the past few quarters, our technology has become mission-critical for AI server manufacturers. We’re rapidly growing our global presence to enable deeper integrations into our customers’ complex manufacturing environments.
We’re seeking a Data Quality Team Lead to be a player-coach: manage and grow a global Data Quality team, including an existing team in Shenzhen and US, while also rolling up their sleeves to perform hands-on data quality work. This hybrid leadership role directly impacts the quality of results our customers see in the Instrumental platform and is key to scaling our world-class manufacturing AI solutions.
This position is ideal for a professional with experience in electronics manufacturing or quality control with people leadership experience. The ideal candidate is multi-faceted, technically savvy, organized, deeply customer-oriented, and fluent in Mandarin to effectively lead our China-based team.
What You’ll Be Doing:
Team Leadership & Cross-functional Coordination

• Hire, lead, coach, and develop a team of Data Quality Specialists, starting with an initial team in Shenzhen, China.
• Set clear expectations, allocate workloads, and ensure consistent, high-quality execution across the team.
• Provide ongoing performance feedback, training, and mentorship to help team members grow in their roles.
• Work closely with Customer Success, Product, and Engineering teams to communicate data quality issues, customer context, and opportunities to improve product performance or operational efficiency
• Serve as a primary communication bridge between the U.S. and Shenzhen teams, ensuring operational alignment.

Hands-On Data Quality Work

• Set Up Customer Program Environments: Partner closely with global Customer Success teams to prepare customer environments for high-quality data ingestion and anomaly detection.
• Label and Review Perform detailed hands-on classification and review of product images to produce training data for AI models and validate model outputs.
• Maintain Quality Standards: Adhere to structured guidelines while ensuring that quality control processes are followed consistently across the team.
• Data Reporting: Clean, analyze, and summarize customer image data to support defect trend analysis and program ROI reporting.
• Issue Escalation & Process Improvement: Identify unusual data patterns, environmental changes (e.g., SKU updates, lighting shifts), and ambiguous cases. Ensure timely escalation and develop improvements to workflows and documentation.

What You Have:

• 2–4 years of experience in manufacturing, quality inspection, process engineering, or similar roles—ideally within the high-tech electronics industry.
• Prior experience hiring, managing, and leading teams
• Excellent spoken and written Mandarin and English
• Meticulous attention to detail and the ability to perform repetitive tasks with consistency and accuracy.
• Strong interpersonal skills and comfort working with global, cross-functional teams.
• Technically savvy and eager to learn new tools, systems, and processes.
• Ability to learn quickly, follow structured workflows, and apply feedback to improve program results.

You’re encouraged to apply even if your experience doesn’t precisely match the job description.
Instrumental offers competitive, location-based compensation. The following is a representative annual base salary range: $140,000-$160,000
Job leveling and salary opportunity are evaluated through our interview process—we review each applicant's experience, knowledge, skills, and abilities. Instrumental’s benefits include: Health, Vision, Dental, Public Transit/Commuter Plans, and Parental Leave.