Engineering Manager, Identification Accuracy
Lead and grow a multidisciplinary team to improve identification accuracy
Lead a team of ML engineers and data scientists to enhance Fingerprint's identification accuracy, directly impacting enterprise customer trust.
Why This Role?
Directly impact enterprise customer trust through improved identification accuracy
Required Skills
Keywords
View Original Description from 4dayweek.io
Original description from 4dayweek.io
**Fingerprint** empowers developers to stop online fraud at the source. We work on turning radical new ideas in the fraud detection space into reality. Our products are developer-focused and our clients range from solo developers to publicly traded companies. **We are a globally dispersed, 100% remote company** with a strong open-source focus. Our flagship open-source project is [FingerprintJS](https://github.com/fingerprintjs/fingerprintjs) (27K stars on GitHub). [We have raised $77M](https://www.crunchbase.com/organization/fingerprintjs) and are backed by Craft Ventures (previously invested in [Tesla,](https://www.tesla.com/) [Facebook,](https://facebook.com/) [Airbnb](https://www.airbnb.com/)), Nexus Venture Partners (previously invested in [Postman](https://www.postman.com/), [Apollo.io,](https://www.apollo.io/) [MinIO](https://min.io/), Druva) and Uncorrelated Ventures (previously invested in [Redis,](https://redis.io/) [Rollbar](https://rollbar.com/)& [Gradle](https://gradle.org/)). _We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Fingerprint recruiting email communications will always come from the @fingerprint.com domain. Any outreach claiming to be from Fingerprint via other sources should be ignored._ * * * ## Engineering Manager, Identification Accuracy **The Role** Do you thrive at the intersection of people leadership and applied machine learning? Do you get excited about building and mentoring multidisciplinary teams — ML engineers, data scientists, analysts, and analytics engineers — working together to solve some of the hardest problems in fraud detection?At Fingerprint, the **Identification Accuracy team** is the engine behind the ML model powering our Identification API — Fingerprint's flagship product. This team is responsible for the accuracy, reliability, and continuous improvement of that model, directly impacting the trust our enterprise customers place in our platform.We are looking for an **Engineering Manager** to lead this team. In this role, you will foster a culture of high performance and scientific rigor, helping a diverse set of technical contributors grow while driving the roadmap that keeps Fingerprint's identification accuracy best-in-class. **What You'll Do** - **Lead and grow the Identification Accuracy team** — a multidisciplinary group of ML Engineers, Data Scientists, Analysts, and Analytics Engineers — fostering psychological safety, technical excellence, and a culture of continuous improvement. - **Own the team's roadmap** in close partnership with senior engineering leadership and cross-functional stakeholders, driving innovative solutions to identification-specific challenges and continuously raising the bar on model quality. - **Drive model accuracy outcomes** by enabling your team to design, train, evaluate, and ship ML models that improve identification accuracy at scale across billions of devices. - **Build bridges across the organization** — partnering closely with the Identification Engineering team (who operates the API your models power) as well as Product, and customer-facing teams to translate customer needs into technical priorities. **Communicate effectively** across technical and non-technical audiences, translating model performance and roadmap tradeoffs into language that resonates with business stakeholders and executive leadership. **Requirements** - Minimum of **2 years of experience in a leadership role in a ML or data science team** in an agile, fast-paced environment. - At least **5 years of professional experience** in software engineering, machine learning, or a related technical discipline. - Demonstrated ability to lead technical teams that ship **production ML systems** — from data pipelines and feature engineering through model training, evaluation, and deployment. - Proven track record of building and developing h