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As an Applied Scientist at Dialpad, you'll be an integral part of our AI team, conducting R&D to power the next generation of autonomous voice agents and delivering features for transcribed voice and chat message data in the business communications domain. We have several research themes, including developing multi-modal, real-time agentic systems that can listen, reason, and take action during live customer interactions. We are also developing real-time knowledge retrieval models to power live coaching features for customer support and sales agents. Beyond the technical skills, we are a team that values collaboration, continuous learning, and the application of diverse perspectives to solve complex problems. Collaboration will be key as you work alongside our engineering, design, and product teams to build groundbreaking applications.
Job Responsibility:
Develop, implement, and refine state-of-the-art Natural Language Processing and Machine Learning algorithms for Dialpad's products
Conduct rigorous evaluation and monitoring of model performances and troubleshoot issues with a keen understanding of resultant business impacts
Manage massive textual data sets
Build advanced LLM-based features, including reasoning, multilingual and multimodal processing, and agents
Collaborate with cross-functional teams, including engineering, product, and design, to effectively deploy and scale models and algorithms in production
Submit papers to top-tier academic conferences and journals and contribute to the broader scientific community by reviewing submissions
Requirements:
Master’s or PhD degree in Linguistics, Computational Linguistics, Computer Science, Machine Learning, or related fields
2+ years of NLP industry experience for Master’s degree holders or 1+ years for PhD degree holders
Demonstrated experience with machine learning, Python, PyTorch, and other relevant tools and technologies
A broad understanding of current LLM model architectures and techniques for tuning and optimizing LLMs
Strong problem-solving and analytical abilities, with the capacity to handle complex technical and analytical problems
Excellent communication and collaboration skills to effectively work in a multi-disciplinary team
Familiarity with version control tools like Git for collaborative projects