SentiLink Offices

SentiLink is headquartered in Austin and has 7 office locations.

Remote Workplace

Employees work remotely.

SentiLink supports a variety of ways to work, ranging from fully remote to in-office. We have offices in multiple cities and if you’re located near one of these offices, we would love for you to spend time in the office regularly.


U.S. Office Locations

HQ
Austin

Austin Office

807 Brazos St, Austin, TX, United States, 78701 2508

Chicago

Chicago Office

Chicago, IL, United States

Los Angeles

Los Angeles Office

Coworking space in the Encino area.

New York

New York Office

Nice coworking space in SoHo.

San Francisco

San Francisco, CA

33 New Montgomery St, San Francisco, CA, United States, 94105

San Ramon

San Ramon (East Bay) Office

San Ramon, CA, United States

Seattle

Seattle (Bellevue) Office

Seattle, WA, United States

Recently posted jobs

14 Hours AgoSaved
Remote
United States
Fintech • Information Technology • Software
Lead and grow a model risk and governance team, set strategy, and run model validation, performance and drift monitoring, fair-lending assessments, governance documentation, model inventory, and change management. Own customer and regulator-facing governance relationships, prepare validation reports, track remediation, balance strategic roadmap with operational demands, and perform hands-on technical work as needed.
16 Hours AgoSaved
Remote
United States
Fintech • Information Technology • Software
Build, train, and productionize machine learning models for fraud detection and identity verification. Perform data acquisition, feature engineering, experimentation, monitoring, and analyses to inform product, sales, and risk decisions. Collaborate with engineering, data acquisitions, and risk operations to maintain data quality and ship production-ready code. Research new fraud types and contribute to new product development across the ML lifecycle.
16 Hours AgoSaved
Remote
United States
Fintech • Information Technology • Software
Build and deploy production ML models for fraud and identity risk across the full ML lifecycle. Research new fraud types, engineer features, write production-ready code, collaborate with cross-functional teams, and inform product, data acquisition, and business decisions.