Job opportunity
Robotics Collection Lead
Welocalize Life Sciences
Job Responsibilities
The Robotics Data Quality Lead is responsible for defining, implementing, and continuously improving quality standards across all robotics data collection workflows. This role ensures that all collected data (video, sensor, teleoperation outputs, and annotations) meets client-defined accuracy, consistency, and usability requirements for AI model training.
Key Responsibilities
Quality Strategy & Ownership
Define and own the end-to-end data quality strategy across robotics data collection and annotation workflows
Establish quality KPIs, SLAs, and acceptance criteria aligned with NVIDIA requirements
Develop and track quality OKRs , ensuring alignment with overall program goals
Proactively identify risks and implement preventative quality measures
Quality Operations & Execution
Design and implement quality assurance frameworks , including audits, sampling methodologies, and validation processes
Oversee daily quality performance , ensuring consistency across operators, moderators, and workflows
Partner with Workflow Managers to ensure task instructions and execution align with quality standards
Ensure high-quality outputs across: Teleoperation sessions Robotics interaction data Sensor and video capture Annotation and labeling outputs
Performance Monitoring & Continuous Improvement
Monitor and report on quality metrics (accuracy, consistency, error rates, throughput impact)
Conduct root cause analysis (RCA) on quality issues and implement corrective and preventive actions (CAPA)
Drive continuous improvement initiatives across tools, workflows, and training
Identify opportunities to improve efficiency without compromising quality
Team Leadership & Enablement
Lead and mentor a team of Robotics Quality Specialists
Define training programs and onboarding for new quality team members
Provide coaching and performance management for direct reports
Promote a quality-first culture across all operational layers
Client & Stakeholder Engagement
Serve as the primary escalation point for quality-related issues
Interface directly with NVIDIA stakeholders on: Quality performance Reporting and insights Escalations and resolution plans
Prepare and present regular quality reports and business reviews
Anticipate client needs and proactively recommend improvements
Process, Documentation & Compliance
Maintain and evolve quality documentation , including guidelines, SOPs, and evaluation frameworks
Ensure alignment with safety and compliance standards in robotics environments
Support cross-functional collaboration with: Safety & Compliance teams Program leadership Engineering / client teams
Requirements
Experience
Experience managing quality in large-scale data operations, robotics, AI/ML, or similar environments
Proven ability to lead cross-functional teams in fast-paced, client-facing settings
Strong background in quality frameworks, process improvement, and data-driven decision making
Experience with robotics workflows, teleoperation, or sensor-based data collection preferred
Core Skills
Strong analytical mindset with ability to interpret and act on data
Experience with RCA, CAPA, and continuous improvement methodologies
Excellent communication skills with ability to influence stakeholders
Ability to manage multiple priorities and drive outcomes under tight timelines
High attention to detail with a focus on scalable quality systems
Key Competencies
Strategic thinking with strong execution focus
Ownership mindset and accountability for outcomes
Ability to drive quality across complex, multi-layered workflows
Strong leadership, coaching, and team development skills
Customer-centric approach with proactive problem solving
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Apply on source site The Robotics Data Quality Lead is responsible for defining, implementing, and continuously improving quality standards across all robotics data collection workflows. This role ensures that all collected data (video, sensor, teleoperation outputs, and annotations) meets client-defined accuracy, consistency, and usability requirements for AI model training.
Key Responsibilities
Quality Strategy & Ownership
Define and own the end-to-end data quality strategy across robotics data collection and annotation workflows
Establish quality KPIs, SLAs, and acceptance criteria aligned with NVIDIA requirements
Develop and track quality OKRs , ensuring alignment with overall program goals
Proactively identify risks and implement preventative quality measures
Quality Operations & Execution
Design and implement quality assurance frameworks , including audits, sampling methodologies, and validation processes
Oversee daily quality performance , ensuring consistency across operators, moderators, and workflows
Partner with Workflow Managers to ensure task instructions and execution align with quality standards
Ensure high-quality outputs across: Teleoperation sessions Robotics interaction data Sensor and video capture Annotation and labeling outputs
Performance Monitoring & Continuous Improvement
Monitor and report on quality metrics (accuracy, consistency, error rates, throughput impact)
Conduct root cause analysis (RCA) on quality issues and implement corrective and preventive actions (CAPA)
Drive continuous improvement initiatives across tools, workflows, and training
Identify opportunities to improve efficiency without compromising quality
Team Leadership & Enablement
Lead and mentor a team of Robotics Quality Specialists
Define training programs and onboarding for new quality team members
Provide coaching and performance management for direct reports
Promote a quality-first culture across all operational layers
Client & Stakeholder Engagement
Serve as the primary escalation point for quality-related issues
Interface directly with NVIDIA stakeholders on: Quality performance Reporting and insights Escalations and resolution plans
Prepare and present regular quality reports and business reviews
Anticipate client needs and proactively recommend improvements
Process, Documentation & Compliance
Maintain and evolve quality documentation , including guidelines, SOPs, and evaluation frameworks
Ensure alignment with safety and compliance standards in robotics environments
Support cross-functional collaboration with: Safety & Compliance teams Program leadership Engineering / client teams
Requirements
Experience
Experience managing quality in large-scale data operations, robotics, AI/ML, or similar environments
Proven ability to lead cross-functional teams in fast-paced, client-facing settings
Strong background in quality frameworks, process improvement, and data-driven decision making
Experience with robotics workflows, teleoperation, or sensor-based data collection preferred
Core Skills
Strong analytical mindset with ability to interpret and act on data
Experience with RCA, CAPA, and continuous improvement methodologies
Excellent communication skills with ability to influence stakeholders
Ability to manage multiple priorities and drive outcomes under tight timelines
High attention to detail with a focus on scalable quality systems
Key Competencies
Strategic thinking with strong execution focus
Ownership mindset and accountability for outcomes
Ability to drive quality across complex, multi-layered workflows
Strong leadership, coaching, and team development skills
Customer-centric approach with proactive problem solving
#J-18808-Ljbffr