Deep Learning Engineer

Build and deploy cutting-edge deep learning architectures to solve complex business problems, such as converting unstructured data into structured formats without hand-tuning features or models. You will develop state-of-the-art models, continuously experiment, and incorporate the latest advancements in the field.

Responsibilities:

• Build and deploy advanced deep learning architectures for complex business use cases.
• Develop state-of-the-art models for processing unstructured data and extracting structured information.
• Continuously experiment with new techniques and integrate recent research advancements into production systems.
• Design and implement large-scale multimodal architectures that understand both text and images.
• Build automated model selection and fine-tuning systems based on data type and volume.
• Develop models for document processing, including invoices, receipts, passports, and driving licenses.
• Create hierarchical information extraction systems for complex document structures.
• Build robust solutions for extracting complex tables from challenging document layouts and warped images.
• Enable few-shot learning using state-of-the-art fine-tuning techniques.

Requirements:

• 5-8 years of experience in deep learning.
• Strong foundational knowledge of deep learning concepts and architectures, including LLMs and VLMs.
• Demonstrated expertise in at least one specialized area of deep learning, such as NLP, computer vision, or multimodal models.
• Experience building and deploying production-grade deep learning systems at scale.
• Familiarity with large language models such as GPT, LLaMA, and Claude, and their applications.
• Strong software engineering practices, including version control, CI/CD, and code quality.
• Ability to rapidly learn and apply new technologies and approaches.