Elizabeth Lingg
Director, Applied Research at Thomson Reuters
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolElizabeth Lingg is a Director of Applied Research based in the San Francisco Bay Area with 11 years of experience building production-grade AI systems and distributed software across Apple, Microsoft, and enterprise startups. She leads teams that translate frontier research into practical, regulated products—most recently driving transactional legal generative AI, agentic retrieval, and specialized small-model tuning for professional-grade accuracy at Thomson Reuters. Her background spans full-stack systems, knowledge graphs, and large-scale distributed scheduling (including hands-on contributions to the Chronos Mesos scheduler), enabling a rare blend of deep systems engineering and ML research. Elizabeth has a strong track record automating evaluation pipelines and human-in-the-loop frameworks to measure groundedness and domain fidelity, delivering measurable lifts for Fortune 500 customers. Trained at Stanford and Carnegie Mellon, she combines academic rigor with a knack for shipping robust, auditable AI workflows in high-stakes domains like healthcare and legal.
11 years of coding experience
17 years of employment as a software developer
Deep Learning Course, Deep Learning Course at UdacityB.S. Computer Science with a Minor in Mathematics, B.S. Computer Science with a Minor in Mathematics at Carnegie Mellon UniversityM.S. Computer Science, Specialization in Artificial Intelligence, M.S. Computer Science, Specialization in Artificial Intelligence at Stanford University
Github Skills (6)
unit-testing10
zone10
timezone10
iso10
job-scheduling10
scala10
Programming languages (6)
Github contributions (5)
mesos/chronos
Sep 2014 - Mar 2016
Fault tolerant job scheduler for Mesos which handles dependencies and ISO8601 based schedules
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3 releases, 99 commits, 61 PRs in 1 year 5 months
Contributions summary:Elizabeth's commits primarily focus on enhancing time zone support within the Chronos job scheduler. They added functionality to parse and handle time zones in ISO8601 expressions, enabling users to schedule jobs based on specific time zones. Further contributions include adding unit tests to validate the time zone parsing logic and ensuring the scheduler correctly interprets and executes jobs with time zone specifications. These changes involved modifying core logic and adding test cases within the project.
fault-tolerantdependenciesfaultschedulerschedules
mesosphere-backup/hdfs-deprecated
Oct 2014 - Nov 2015
Contributions:2 releases, 226 commits, 94 PRs in 1 year
cssjavascriptarchived
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