Data Quality Partner Lead

Figureai

San Jose (CA)

On-site

USD 120,000 - 180,000

Full time

14 days+

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Job summary

Figureai in San Jose, CA is seeking a Data Quality Partner Lead to build an external annotation and review vendor network from scratch. The ideal candidate has over 5 years in vendor management and is skilled at building partnerships.

Your responsibilities will include developing the vendor strategy, managing evaluations, and overseeing partner performance to ensure high data quality standards. A passion for AI and team collaboration are essential.

Qualifications

  • 5+ years in vendor management or operations roles.
  • Track record of building or scaling vendor functions.
  • Comfortable using AI coding tools.
  • Excellent written and verbal communication skills.

Responsibilities

  • Own Figure’s external annotation and review vendor strategy.
  • Build the vendor pipeline from scratch.
  • Run structured evaluations of prospective vendors.
  • Translate Data Quality standards into vendor specs.
  • Manage partner relationships and operations at scale.

Skills

Vendor management
BPO/outsourcing partnerships
Strategic sourcing
Excellent communication skills
Operating with ambiguity

Job description

Figure is an AI Robotics company developing a general purpose humanoid. Our Humanoid is designed for corporate tasks targeting labor shortages and jobs that are undesirable or unsafe. We are based in San Jose, CA and require 5 days/week in-office collaboration.

We are looking for a Data Quality Partner Lead to build Figure’s external annotation and review vendor network from scratch. You will source, evaluate, onboard, and manage the BPOs, specialized labeling firms, and crowdsourcing platforms that extend our data quality capacity.

Responsibilities:
  • Own Figure’s external annotation and review vendor strategy end to end, from sourcing through onboarding through ongoing performance management
  • Build the vendor pipeline from zero by identifying and engaging BPOs, specialized labeling firms, crowdsourcing platforms, and emerging providers in the AI data ecosystem
  • Run structured evaluations of prospective vendors, including pilots, quality benchmarking, and capacity testing, and make clear recommendations on who to scale with
  • Translate the Data Quality team’s standards and methodologies into vendor specs, making sure the bar we set internally is the bar our partners deliver against
  • Stand up the operating model for managing partners at scale, including scorecards, escalation paths, and the tooling
Requirements:
  • 5+ years in vendor management, BPO/outsourcing partnerships, strategic sourcing, or operations roles with significant external partner ownership
  • Track record of building or scaling a vendor function from an early stage, ideally in a domain where quality was the primary lever
  • Comfortable rapidly building and deploying apps/agents using AI coding tools to build internal tools, dashboards, and trackers (zero technical academic background necessary)
  • Excellent written and verbal communication skills, especially when setting expectations with external partners
  • Comfortable operating with ambiguity and managing multiple concurrent partner relationships
  • Low ego, team player with can-do attitude
Bonus Qualifications:
  • Direct experience managing data annotation, labeling, or content review vendors
  • Background at a frontier AI lab, autonomous vehicle company, or other organization where data quality at scale was a core problem
  • A passion for helping scale the deployment of learning humanoid robots

The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

The US base salary range for this full-time position is between $120,000 – $180,000 annually.

The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

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