Job
Description
About the Role We are looking for a highly skilled and accomplished Applied Scientist with a strong track record in developing advanced deep learning and generative AI algorithms. This is a rare opportunity to work at the forefront of AI innovation, collaborating closely with cross-functional product teams to bring cutting-edge models to life across domains such as computer vision, NLP, and audio signal processing . Why Join Us? Join a fast-growing, future-focused company with one of the most extensive AI service repositories. Be part of a dynamic, innovation-driven team on a mission to become the leading AI Platform-as-a-Service (AI PaaS) provider for global enterprises and developers. Key Responsibilities Design and optimize deep learning, foundational, and generative AI models for production use. Develop multi-modal AI solutions (text, audio, image/video) with advanced semantic understanding. Conduct end-to-end R&D to convert novel ideas into deployable, real-world use cases. Collaborate with researchers and engineers to ensure model performance, scalability, and reliability . Work closely with product teams to embed AI algorithms into customer-facing applications and platforms. Drive POC development and pilot solutions for customers across industries: finance, energy, healthcare, environment , etc. Support pre-sales and post-sales technical engagements , showcasing the impact of AI to client stakeholders. Identify and recommend AI opportunities for automation, optimization, and innovation across customer environments. Skills and Experience Required M.Sc. or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or related field. 6+ years of experience building AI/ML models for NLP, computer vision, or speech/audio applications. Demonstrated success in applied research with a portfolio of patents, POCs, or publications in top-tier journals/conferences. Strong programming expertise in Python , with libraries such as TensorFlow, PyTorch, Transformers, and HuggingFace . Hands-on experience with ML lifecycle , from data preparation to deployment and monitoring. Proficiency in working with large datasets and high-dimensional data from multiple modalities. Understanding of cloud-based ML infrastructure (AWS, Azure, GCP). Let’s Talk If you're a scientifically curious, technically sharp, and product-driven AI expert who thrives on building and deploying impactful AI systems, we’d love to hear from you. Let me know if you’d like this formatted into a Word doc or PowerPoint slide. Show more Show less
