Team Lead

Role & responsibilities

Job Summary:

We are looking for a versatile and experienced professional to serve as the Lead Data Annotation & AI Model Training, combining the responsibilities of a Team Leader. In this role, you will oversee and guide a team engaged in high-quality data annotation and preparation for large-scale machine learning models across text, image, video, and 3D (LIDAR) domains.

You will be responsible for developing guidelines, training team members, ensuring annotation quality, collaborating with Customers, and continuously improving data operations for tasks such as LLM fine-tuning, bounding box creation, semantic labeling, image/video summarization, and LIDAR point cloud annotations.

Key Responsibilities:

1. Team Leadership

• Lead a team of annotators, junior SMEs, and quality checkers; oversee day-to-day operations, task assignments, and productivity.
• Monitor project timelines and resource allocation to meet deadlines and quality expectations.
• Perform quality audits, give feedback, and drive performance improvements across the team.
• Act as the primary liaison between annotation teams and upstream/downstream stakeholders.

Required Qualifications:

• Bachelors or Masters degree in Computer Science, AI/ML, or related fields.
• 1-6 years of experience in AI data annotation.

Technical Skills:

• Hands-on experience with annotation tools.
• Expertise in LLM data formats (prompt-response, instruction tuning), NER, sentiment tagging, etc.
• Strong knowledge of bounding box creation, image segmentation, video tagging, and summarization workflows.
• Familiarity with LIDAR labeling (e.g., 3D bounding boxes, point cloud segmentation).
• Basic scripting (Python preferred) for automating QA and dataset processing is a plus but not mandatory.
• Understanding of data lifecycle, dataset versioning, and the impact of data quality on model training.

Soft Skills:

• Excellent communication and interpersonal skills.
• Strong analytical thinking and problem-solving capabilities.
• Ability to coach, mentor, and lead by example.
• Comfortable working in fast-paced, iterative environments.

Preferred Qualifications:

• Exposure to autonomous driving, robotics, or surveillance datasets.
• Familiarity with MLOps, active learning, or human-in-the-loop data pipelines.
• Prior experience working with generative AI model training (LLMs, VLMs)