Remote Senior Engineering Team Lead — AI Data & Quality

Lever, Inc.; España; Híbrido; EUR 70.000 - 120.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive compensation

Remote-friendly options

Descripción de la vacante

Lever, Inc. is seeking an Expert Team Lead, Engineering in Spain to lead a high-performing team focused on producing high-quality training data and evaluations for AI models.

You will combine hands-on engineering with coaching, performance management, and scalable data operations. You will translate model requirements into labeling strategies, build training materials, and drive continuous improvements using KPIs.

Formación

• Bachelor's degree in an engineering discipline.
• At least 2 years of professional engineering experience or advanced degree.
• Understanding of AI/ML concepts and data-quality importance.
• Experience with data-quality metrics, annotation workflows, and guideline-driven processes.
• Experience leading teams, coaching, and performance management.
• Ability to manage multiple projects and drive improvements.

Responsabilidades

• Own end-to-end quality and delivery for assigned Human Data projects.
• Lead and manage AI Tutors team including contractors.
• Oversee labeling and review activities to maintain high standards.
• Ensure adherence to guidelines, taxonomies, and QA processes.
• Identify bottlenecks and implement process improvements.
• Monitor performance with KPI dashboards and metrics.

Conocimientos

Team leadership

Quality assurance

Data labeling

Process improvement

KPIs tracking

Coaching

Educación

Engineering degree

2+ years in engineering

Descripción del empleo

Lever, Inc. is seeking an Expert Team Lead, Engineering in Spain to lead a high-performing team focused on producing high-quality training data and evaluations for AI models.

You will combine hands-on engineering with coaching, performance management, and scalable data operations. You will translate model requirements into labeling strategies, build training materials, and drive continuous improvements using KPIs.