We are looking for a search relevance engineer to work with a team to improve a search based question answering platform. At Moveworks, we build search technology to answer enterprise users’ tech questions instantly, by combining modern information retrieval methodology with the latest advancement in natural language understanding. Our core Search product value is achieved through the capability of accurately retrieving, matching and ranking text snippets extracted from heterogeneous knowledge sources, as direct answers to users’ requests. You will play a critical role in boosting answer quality by meeting the challenges such as lexical gap, semantic text understanding, and data sparsity.
We’re building a team that indexes on moving fast, solving challenging product/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.Who we are:
Moveworks is revolutionizing how companies support their employees — with the first AI platform that makes getting help at work effortless. Using advanced conversational AI built for the enterprise, Moveworks gives employees exactly what they need, from IT support to HR help to policy information. Our platform allows customers like Snowflake, Slack, DocuSign, LinkedIn, Instacart, Illumina, Epic Games, Hearst Media to move forward on what matters.
Founded in 2016, Moveworks has raised $315 million in funding, at a valuation of $2.1 billion. We’ve been named to the Forbes AI 50 list for three consecutive years, while earning recognition as the Best Chatbot Solution at the 2021 AI Breakthrough Awards. Above all, we’ve built an AI company that puts people first, which is why both Inc. and the San Francisco Business Times called Moveworks one of the Best Workplaces of 2021.
What you’ll do:
Come join one of the fastest-growing teams on the planet!
- Craft new ranking features and optimizing existing ones to enhance relevance metrics
- Develop algorithm framework to support diversified ranking features
- Design platform and tooling to enable parallel ranking experiments
- Develop metrics to evaluate ranking performance
- First-hand experience in traditional information retrieval techniques, or machine learning based ranking models
- Capable of deriving insights from query logs analysis and identifying areas of improvement for search quality
- Background in text processing, information retrieval, natural language understanding, or machine learning
- Experience in Golang.