AI/ML Engineer - Data Science

Role Overview: As an experienced AI/ML Engineer cum Data Scientist at our company, you will be responsible for developing real-world AI solutions encompassing Computer Vision, Document AI, and Generative AI. Your focus will be on taking these solutions from model development to production deployment, particularly for image, video, and unstructured document data. Key Responsibilities: - Develop and deploy AI solutions for image understanding, OCR, document structure recognition, and video analytics. - Build end-to-end ML pipelines covering data strategy, model training, evaluation, and optimization. - Work on GenAI use cases such as Prompt Engineering and RAG over unstructured data. - Optimize models for accuracy, latency, and scalability. - Collaborate closely with product and engineering teams to translate business problems into AI solutions. - Mentor junior engineers and contribute to AI best practices. Qualification Required: - Strong hands-on experience in Deep Learning and Computer Vision. - Proficiency in OCR, object detection, segmentation, and document AI. - Exposure to GenAI concepts including Prompting, RAG, and LLM workflows. - Proficiency in PyTorch/TensorFlow and Python. - Experience in building and deploying ML solutions in production. Company Details: The company is focused on leveraging AI technologies to develop innovative solutions across various domains. They value collaboration and mentorship, offering opportunities to work on cutting-edge projects and contribute to AI best practices. Role Overview: As an experienced AI/ML Engineer cum Data Scientist at our company, you will be responsible for developing real-world AI solutions encompassing Computer Vision, Document AI, and Generative AI. Your focus will be on taking these solutions from model development to production deployment, particularly for image, video, and unstructured document data. Key Responsibilities: - Develop and deploy AI solutions for image understanding, OCR, document structure recognition, and video analytics. - Build end-to-end ML pipelines covering data strategy, model training, evaluation, and optimization. - Work on GenAI use cases such as Prompt Engineering and RAG over unstructured data. - Optimize models for accuracy, latency, and scalability. - Collaborate closely with product and engineering teams to translate business problems into AI solutions. - Mentor junior engineers and contribute to AI best practices. Qualification Required: - Strong hands-on experience in Deep Learning and Computer Vision. - Proficiency in OCR, object detection, segmentation, and document AI. - Exposure to GenAI concepts including Prompting, RAG, and LLM workflows. - Proficiency in PyTorch/TensorFlow and Python. - Experience in building and deploying ML solutions in production. Company Details: The company is focused on leveraging AI technologies to develop innovative solutions across various domains. They value collaboration and mentorship, offering opportunities to work on cutting-edge projects and contribute to AI best practices.