Key Responsibilities:
- Lead and mentor a dynamic Data Science team in developing scalable, reusable tools and capabilities to advance machine learning models, specializing in computer vision, natural language processing, API development and Product building.
- Drive innovative solutions for complex CV-NLP challenges, including tasks like image classification, data extraction, text classification, and summarization, leveraging a diverse set of data inputs such as images, documents, and text.
- Collaborate with cross-functional teams, including DevOps and Data Engineering, to design and implement efficient ML pipelines that facilitate seamless model integration and deployment in production environments.
- Spearhead the optimization of the model development lifecycle, focusing on scalability for training and production scoring to manage significant data volumes and user traffic. Implement cutting-edge technologies and techniques to enhance model training throughput and response times.
Required Experience & Expertise:
- 3+ years of experience in developing computer vision models and applications.
- Extensive knowledge and experience in Data Science and Machine Learning techniques, with a proven track record in leading and executing complex projects.
- Deep understanding of the entire ML model development lifecycle, including design, development, training, testing/evaluation, and deployment, with the ability to guide best practices.
- Expertise in writing high-quality, reusable code for various stages of model development, including training, testing, and deployment.
- Advanced proficiency in Python programming, with extensive experience in ML frameworks such as Scikit-learn, TensorFlow, and Keras and API development frameworks such as Django, Fast API.
- Demonstrated success in overcoming OCR challenges using advanced methodologies and libraries like Tesseract, Keras-OCR, EasyOCR, etc.
- Proven experience in architecting reusable APIs to integrate OCR capabilities across diverse applications and use cases.
- Proficiency with public cloud OCR services like AWS Textract, GCP Vision, and Document AI.
- History of integrating OCR solutions into production systems for efficient text extraction from various media, including images and PDFs.
- Comprehensive understanding of convolutional neural networks (CNNs) and hands-on experience with deep learning models, such as YOLO.
- Strong capability to prototype, evaluate, and implement state-of-the-art ML advancements, particularly in OCR and CV-NLP.
- Extensive experience in NLP tasks, such as Named Entity Recognition (NER), text classification, and on finetuning of Large Language Models (LLMs).
- This senior role is tailored for visionary professionals eager to push the boundaries of CV-NLP and drive impactful data-driven innovations using both well-established methods and the latest technological advancements.
