To apply for this job, you need to complete both steps below:

STEP 1:

Please click the link to submit your application directly to the company: 

https://www.linkedin.com/jobs/view/4395931974

Your application will only be received by Recruiter if submitted via above link. 

STEP 2:

Kindly scroll to the bottom of this page and complete the short VinUni Tracking Form.

Filling out this form alone does not count as applying. Kindly remind this form is not part of the company’s application process. It only helps Careers, Alumni, Industry and Development (CAID) Department discover more opportunities and follow up in case of system issues.

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.
• Evaluate VLM performance using both quantitative metrics and qualitative behavior analysis, focusing on correctness, consistency, robustness, latency, and stability in real-world deployments.
• Conduct detailed error analysis and provide actionable recommendations for data improvement, prompt refinement, model retraining, and release (go/no-go) decisions.

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