Data Scientist

We are looking for a highly skilled Data Scientist with expertise in Vision Language Models (VLMs), Computer Vision, and Multimodal AI to join our AI team. In this role, you will work on designing, developing, and optimizing next-generation AI models that can understand and reason across multiple data modalities, including images, text, and video. You will collaborate closely with machine learning engineers, data engineers, and product teams to build intelligent AI solutions that solve complex real-world problems.

The ideal candidate has a strong background in deep learning, computer vision, multimodal foundation models, and data-centric AI development. You should be comfortable working with large datasets, experimenting with state-of-the-art architectures, and deploying scalable AI solutions.

Key Responsibilities

• Design, build, and optimize AI models using Vision Language Models (VLMs) and multimodal learning techniques.
• Develop computer vision pipelines for image classification, object detection, segmentation, visual reasoning, OCR, and image understanding.
• Build multimodal AI systems that effectively combine text, images, videos, and structured data to solve business challenges.
• Research, evaluate, and implement state-of-the-art deep learning models and emerging AI architectures.
• Prepare, clean, annotate, and validate large-scale datasets for machine learning and computer vision applications.
• Develop efficient data preprocessing, augmentation, and feature engineering pipelines to improve model quality.
• Fine-tune pre-trained vision and multimodal foundation models for domain-specific use cases.
• Conduct experiments, evaluate model performance using appropriate metrics, and continuously improve model accuracy and efficiency.
• Collaborate with engineering teams to deploy AI models into production and monitor their performance.
• Document experiments, methodologies, and best practices while staying updated with the latest advancements in AI research.

Required Skills

Must-have Skills

• Strong experience with Vision Language Models (VLMs) and multimodal AI architectures.
• Hands-on expertise in Computer Vision , including image processing and deep learning-based vision tasks.
• Solid understanding of Multimodal AI , integrating text, image, and video data for intelligent applications.
• Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
• Experience working with transformer-based architectures and foundation models.
• Strong knowledge of machine learning algorithms, model evaluation, optimization, and experimentation.
• Familiarity with GPU-based training and distributed deep learning workflows.
• Good understanding of data structures, algorithms, and software engineering best practices.

Good-to-have Skills

• Experience in Dataset Preparation , including data collection, cleaning, annotation, and quality validation.
• Expertise in Dataset Engineering for large-scale AI training pipelines.
• Hands-on experience in Fine-tuning foundation models, vision transformers, and multimodal models using modern techniques such as LoRA, PEFT, or transfer learning.
• Familiarity with MLOps tools, model versioning, and experiment tracking platforms.
• Exposure to cloud platforms such as AWS, Azure, or Google Cloud.
• Knowledge of containerization technologies like Docker and orchestration platforms such as Kubernetes is a plus.

Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or a related field.
• 4–6 years of professional experience in Data Science, Computer Vision, or Applied AI.
• Strong analytical, problem-solving, and communication skills.
• Passion for researching and implementing cutting-edge AI technologies while delivering production-ready solutions.