Machine Learning Engineer, GAI Search Platform - Moveworks

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          "text": "<p><strong>What You Will Do</strong></p><p>We are looking for Machine learning engineers to join our&#xa0;<em>GenAI Search Platform</em>&#xa0;team to improve our search-based question answering systems, utilizing both traditional machine learning and cutting-edge generative AI technologies. At Moveworks, we build conversational search systems to provide instant answers to enterprise users’ questions. We deliver business intelligence support by combining modern information retrieval with the latest advancement in natural language understanding, including LLMs (large language models). By accurately retrieving, matching, ranking, and summarizing text snippets grounded in heterogeneous knowledge sources, our search products are reshaping the enterprise search experience for millions of our customers’ employees.</p><p>The search platform team works closely with the ranking, product, design, infrastructure and data science teams to drive our agentic search products to the next generation of capabilities focusing on performance and enterprise readiness.</p><p>We’re building a team that thrives on moving fast, solving challenging product and engineering problems, and providing value to our customers. To be successful, you'll be partnering with product, user experience, customer success and other engineering teams to identify, define and build elegant solutions.&#xa0;</p><ul><li>Drive the development of our search platform with new LLM-enabled generative AI features in a fast-paced environment. This platform would enable product teams to build new applications and features quickly, ship new prototypes to customers at scale, evaluate and iterate on ranking improvements in a systematic manner, and enforce guarantees on quality, security, privacy and scalability.</li><li>Develop systematic evaluation metrics and methodology for our search models, leveraging LLMs to address unique challenges in the enterprise such as security and privacy.</li></ul><p>&#xa0;</p>",
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