Staff Ai Scientist

As a Staff AI Scientist at Uniphore, you will play a crucial role in designing and developing agentic AI systems and retrieval-augmented generation (RAG) applications for large enterprises. You will have the opportunity to work on AI technologies and contribute directly to enterprise use-cases of generative AI systems deployed at a global scale. Key Responsibilities: - Design and develop agentic AI systems and retrieval-augmented generation (RAG) applications for large enterprises. - Research and implement methods for fine-tuning, alignment, and evaluation of AI agents and RAG systems. - Contribute to the development of our agentic platform, including context management, memory architectures, evaluation frameworks, and trust and safety mechanisms. - Conduct applied AI research by evaluating, adapting, and extending state-of-the-art open-source models. - Lead AI projects from research and prototyping through production deployment as part of cross-functional teams including engineering, product management, and solutions engineering. Qualifications: - Masters or Ph.D. in Computer Science, Electrical Engineering, Computer Engineering, or a related field. - 7+ years of industry experience in AI/ML for candidates with a Masters degree, or 3+ years for Ph.D. candidates. - Competence in probability, statistics, linear algebra, and machine learning. - Expertise in Python and deep learning frameworks such as PyTorch or TensorFlow, with experience using modern ML tooling (e.g., Hugging Face, vLLM). - Experience building production-ready, scalable machine learning systems. - Deep understanding of modern AI techniques in areas such as NLP, multimodal AI, speech (ASR), or computer vision. - Strong publication record in top-tier conferences such as NeurIPS, ICML, ICLR, ACL, EMNLP, or AAAI is preferred. - Experience with model fine-tuning and reinforcement learning is a plus. As a Staff AI Scientist at Uniphore, you will play a crucial role in designing and developing agentic AI systems and retrieval-augmented generation (RAG) applications for large enterprises. You will have the opportunity to work on AI technologies and contribute directly to enterprise use-cases of generative AI systems deployed at a global scale. Key Responsibilities: - Design and develop agentic AI systems and retrieval-augmented generation (RAG) applications for large enterprises. - Research and implement methods for fine-tuning, alignment, and evaluation of AI agents and RAG systems. - Contribute to the development of our agentic platform, including context management, memory architectures, evaluation frameworks, and trust and safety mechanisms. - Conduct applied AI research by evaluating, adapting, and extending state-of-the-art open-source models. - Lead AI projects from research and prototyping through production deployment as part of cross-functional teams including engineering, product management, and solutions engineering. Qualifications: - Masters or Ph.D. in Computer Science, Electrical Engineering, Computer Engineering, or a related field. - 7+ years of industry experience in AI/ML for candidates with a Masters degree, or 3+ years for Ph.D. candidates. - Competence in probability, statistics, linear algebra, and machine learning. - Expertise in Python and deep learning frameworks such as PyTorch or TensorFlow, with experience using modern ML tooling (e.g., Hugging Face, vLLM). - Experience building production-ready, scalable machine learning systems. - Deep understanding of modern AI techniques in areas such as NLP, multimodal AI, speech (ASR), or computer vision. - Strong publication record in top-tier conferences such as NeurIPS, ICML, ICLR, ACL, EMNLP, or AAAI is preferred. - Experience with model fine-tuning and reinforcement learning is a plus.