Vision-Language Model
3 weeks ago
Situated in the heart of Singapore's Central Business District, Rakuten Asia Pte. Ltd. is Rakuten's Asia Regional headquarters. Established in August 2012 as part of Rakuten's global expansion strategy, Rakuten Asia comprises various businesses that provide essential value-added services to Rakuten's global ecosystem. Through advertisement product development, product strategy, and data management, among others, Rakuten Asia is strengthening Rakuten Group's core competencies to take the lead in an increasingly digitalized world.
The Visual Intelligence Engineering Department (VIED), part of the AI and Data Division, delivers scalable computer vision technology to drive measurable business outcomes. Leveraging Rakuten's unique data and expertise, VIED develops innovative solutions in areas like content moderation, OCR, face verification, and Creative AI, with a focus on engineering excellence, reusability, and state-of-the-art CV algorihtm.
VIED's strategy includes advancing Creative AI for personalized, engaging content and building scalable systems for seamless testing and deployment of computer vision models. Committed to collaboration, standardized processes, and continuous improvement, VIED seeks top talent in computer vision and machine learning to create impactful, scalable solutions aligned with Rakuten's goals.
About the Role
We are seeking a driven Vision-Language Model (VLM) Engineer to spearhead the development of a next-generation VLM solution. You will focus on fine-tuning an existing VLM for various compliance-related tasks, unifying multiple models into one cohesive system. This position involves close collaboration with a distributed team, including members who have previously experimented with VLM fine-tuning and are eager to support your work.
Key Responsibilities
•Build upon existing VLM architectures and fine-tune them for compliance tasks
•Unify previously separate compliance models into a single deployment-ready solution.
•Conduct experiments to evaluate and improve the VLM's accuracy, drawing insights from past attempts (e.g., fine-tuning Florence-2).
•Investigate methods for leveraging spatial and geometric understanding in next-generation VLMs.
•Present findings, progress updates, and recommendations to the broader team.
•Explore cutting-edge techniques (e.g., text prompting for image border detection, bounding box generation, and dimension measurement).
Qualifications
•Advanced degree in Computer Science, Machine Learning, or a related field.
•Demonstrable experience in training or fine-tuning large-scale vision-language or multimodal models.
•Proficiency in Python and popular ML frameworks (e.g., PyTorch, TensorFlow)
• Experience with transformer-based architectures, image processing, and NLP techniques.
•Familiarity with MLOps best practices (containerization, continuous integration, deployment).
•Strong communication abilities, with the capacity to convey technical concepts to both technical and non-technical stakeholders.
•Collaborative mindset and a willingness to partner with cross-functional, globally distributed teams.
TensorFlow
Machine Learning
Image Processing
Data Management
Drawing
Computer Vision
Strategy
PyTorch
Compliance
Python
Containerization
Continuous Integration
Product Development
OCR
Computer Vision Technology
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