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Staff Data Engineer

Laurel

🌍 North America 🏠 Remote ⏱ Part-time 💼 Senior 🗓 5 weeks ago

Laurel is on a mission to return time. As the leading AI Time platform for professional services firms, we’re transforming how organizations capture, analyze, and optimize their most valuable resource: time. Our proprietary machine learning technology automates work time capture and connects time data to business outcomes, enabling firms to increase profitability, improve client delivery, and make data-driven strategic decisions. We serve many of the world's largest accounting and law firms, including EY, Aprio, Crowell & Moring, and Frost Brown Todd, and process over 1 billion work activities annually that have never been collected and aggregated before Laurel’s AI Time platform.

Our team comprises top talent in AI, product development, and engineering—innovative, humble, and forward-thinking professionals committed to redefining productivity in the knowledge economy. We're building solutions that empower workers to deliver twice the value in half the time, giving people more time to be creative and impactful. If you're passionate about transforming how people work and building a lasting company that explores the essence of time itself, we'd love to meet you.

ABOUT THE ROLE

Laurel's infrastructure, data, and security team is lovingly named the Time Owls. We make Laurel's infrastructure more reliable, secure, and easy to use. Our team builds and maintains the tools, platforms, and automation that enable engineers across the company to work with AWS, Kubernetes, and other services easily and safely. We contribute to all applications in the company and act as both best-practice advocates and policy enforcers.

This role sits at the intersection of infrastructure and AI. You'll work closely with our AI engineers and data scientists, focusing on making their work fast, efficient, scalable, and secure. You'll own data pipelines, model-serving infrastructure, and the systems that move data reliably through our platform — from ingestion through to production inference....

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