REQUIREMENTS:

Relevant Education & Experience

• Bachelor’s or Master’s degree in Computer Science, AI, Data Science, Robotics, or a related field (or equivalent practical experience).
• Strong analytical mindset with exceptional attention to data quality, edge cases, and model behavior.
• Hands-on experience working with AI data pipelines, Computer Vision systems, Vision-Language Models (VLMs), or multimodal datasets (image, video, text).
• Solid understanding of modern VLM architectures, including vision encoders, large language models, cross-modal alignment, and prompting strategies.
• Experience evaluating AI systems beyond raw quantitative metrics, with a focus on semantic correctness, contextual reasoning, robustness, and real user-facing behavior.
• Proven experience working with large-scale datasets and structured evaluation workflows, including annotation guidelines, validation protocols, and quality control mechanisms.
• Strong communication skills with the ability to collaborate effectively with AI engineers, researchers, and external data vendors.
• Comfortable reading and interpreting technical documentation and research papers in English.

Preferred Qualifications

• Hands-on experience with annotation or review tools (e.g., Label Studio, CVAT, or custom review platforms).
• Basic Python skills for data analysis, scripting evaluation pipelines, or automation.
• Understanding of MLOps practices and model lifecycle management (training, validation, deployment, monitoring).
• Experience managing or collaborating with external data vendors or crowdsourced annotation teams.
• Exposure to robotics, embodied AI, or human–robot interaction use cases.

Personality & Attitude

• Proactive, responsible, business-oriented, and eager to learn.
• Strong communication and creative problem-solving skills, with high attention to detail.

JOB DESCRIPTION:

Multimodal Data Quality & VLM Evaluation

• Ensure the quality of multimodal datasets (image, video, text, captions, instructions) used for VLM training and evaluation, collaborating with internal AI teams and external data vendors.
• Define, implement, and enforce data quality standards for VLM systems, covering visual accuracy, textual correctness, vision–language alignment, semantic consistency, and bias/noise detection.
• Review and audit datasets before and after annotation, identifying systemic issues such as misaligned captions, hallucinated descriptions, weak prompts, inconsistent labeling, and distribution gaps.
• Design structured evaluation datasets and test protocols for VLM use cases, including VQA, instruction following, multimodal reasoning, and human–robot interaction scenarios.

BENEFITS:

• Attractive income, competitive and commensurate with individual capabilities.
• 13th-month salary, gifts on public holidays and special occasions, and performance-based bonuses.
• Meal allowance, annual company trips, health insurance, and exclusive benefits within the Group’s ecosystem.
• Clear career development opportunities aligned with the company’s growth, with access to training programs based on capability and job role.
• A dynamic and open working environment with diverse cultural and sports activities.

Location: TechnoPark Tower, Gia Lam, Hanoi