Data Annotation Manager

motional singapore pte. limited

Singapore

Presencial

SGD 90.000 - 140.000

Jornada completa

Hace 4 días
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Descripción de la vacante

Motional Singapore Pte. Limited is seeking a Data Annotation Manager to lead a high-performing team of data specialists and project managers responsible for labeling data used in autonomous vehicle perception and other ML models.

You will own team productivity, guide the employee lifecycle, and drive operation excellence. The role emphasizes building expert annotation workflows, using data-driven insights to streamline processes, and coaching staff to advance their careers while upholding

Formación

  • Degree in any related technical field.
  • At least 6 years of domain expertise in data operations, labeling, CV dataset creation, or ML annotation workflows.
  • 2 years of leadership experience supervising teams in a tech or autonomous driving domain.
  • Proven ability to manage the full employee lifecycle with coaching and feedback.

Responsabilidades

  • Supervise daily operations of data annotation team members and set priorities to meet SLAs.
  • Drive goals and productivity by owning team performance and quality.
  • Manage employee lifecycle including hiring, onboarding and performance reviews.
  • Solve operational challenges using process data and drive workflow improvements.

Conocimientos

Data operations
Data labeling
Computer vision datasets
ML annotation workflows

Educación

Degree in a related technical field

Descripción del empleo

Mission Summary:

Motional is seeking a Data Annotation Manager to join our Operations team. In this role, you will lead a team of high-performing team data specialists and project managers responsible for overseeing high-quality data used by our autonomous vehicle perception and other machine learning models. As a manager, you will own team productivity and operational effectiveness, manage the team's employee lifecycle independently, and ensure team goals are met. You will build on your expertise in human labeled data and annotation workflows while exemplifying Motional's core values and leadership behaviors.

What you'll be doing:
  • Supervise Daily Operations: Direct the daily activities of data annotation team members, setting priorities to ensure task completion, SLA adherence, and seamless coordination across workstreams.
  • Drive Goals & Productivity: Set and ensure the achievement of operational goals owning the productivity, quality, and effectiveness of your team with minimal manager oversight.
  • Manage Employee Lifecycle: Support the full employee lifecycle independently, including hiring, onboarding, and performance evaluation. Effectively coach and mentor team members to support their career development and provide continuous feedback.
  • Solve Operational Challenges: Utilize established process and data-driven insights to guide problem-solving and streamline annotation workflows. Drive efficiency through automation, removing bottlenecks and cultivate a growth mindset within the team.
What we're looking for:
  • Degree in any related technical field
  • At least 6 years of Domain Expertise: Experience in data operations, data labeling, computer vision dataset creation, or machine learning annotation workflows.
  • 2 years of Leadership Experience: Proven experience supervising team members, setting operational priorities, and guiding daily team output in a fast-paced technology or autonomous driving domain.
  • People Management Capabilities: Demonstrated proficiency in managing the full employee lifecycle, conducting performance reviews, and coaching staff with minimal guidance.
Bonus points:
  • Prior experience working with autonomous driving data, sensor data (LiDAR, Radar, Camera), or 3D bounding box annotation tools.
  • Vendor management experience, including defining performance metrics, building relationships with third-party suppliers, and holding them accountable to SLAs and contract standards.
  • Experience working with diverse cultures and managing projects across multiple time zones.
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