August 7
• Collaborate with product design and engineering teams to understand business and data needs. • Develop, test, and deploy robust conversational agents that meet user needs and project requirements. • Continuously improve the natural language understanding (NLU) and overall performance of conversational agents through customization and optimization techniques. • Implement context-aware conversations and design conversation flows that handle complex user queries effectively. • Develop and execute test plans to assess agent performance, identifying areas for improvement and iterating on data, prompts, and workflows. • Communicate findings to stakeholders effectively. • Stay current with industry developments and technical advancements.
• At least 5 years of professional experience as a Data Scientist or Engineer • Business level English verbal and writing. • A Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field. • A minimum of two years experience as an ML engineer. • Proficiency in data manipulation and analysis tools like SQL and Pandas. • Familiarity with Data Warehousing. • Experience in developing, evaluating, deploying, running, and maintaining ML models. • A strong understanding of AI agents, natural language processing, and machine learning concepts. • At least 5 years of experience using LLMs and LLM-enabled programs in a professional, academic, or personal context, including exploring how they work and how to use them effectively. • Experience with LangChain or other AI agent frameworks. • Experience with LLM observability. • Familiarity with the optimal use of LLMs, the tradeoff between fine-tuning and RAG, etc. • Familiarity with prompt engineering best practices. • Familiarity with data structures for ML and AI programs, including RAG and vector databases. • Experience with building systems and infrastructure is preferred. • Strong problem-solving and critical-thinking skills. • Excellent communication and presentation skills.
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