About this role
Data scientists who thrive on solving complex inference problems with raw and unlabeled data will find a natural fit within this team. Fingerprint builds device intelligence technology that helps global enterprises stop online fraud in real time.
In this role, the engineer will focus on improving the accuracy of the core identification service by developing data-driven algorithms and managing projects from initial concept through deployment. The position exists to drive technical strategies and elevate the company's real-time machine learning capabilities while fostering an engineering-driven culture.
What you will do
- Develop data-driven algorithms for the Fingerprint Identification Service by applying machine learning techniques to raw, noisy, and unlabeled browser and device data.
- Lead the design and implementation of supervised, semi-supervised, and unsupervised learning approaches to enhance identification capabilities.
- Own data science initiatives completely, guiding them from initial concepts and experimentation through to deployment inside the real-time platform.
- Design experiments and solutions for machine learning engineering challenges, including real-time model inference and training pipeline automation.
- Conduct exploratory data analysis to investigate ad-hoc questions and resolve anomalous dataset behaviors.
- Help build a data-driven culture across the engineering team by sharing effective tools and data science methodologies.
- Participate in a shared on-call rotation with equitable coverage schedules designed to minimize off-hours disruption.
What you need
- Bring five or more years of professional experience spanning machine learning, data science, and backend development.
- Possess advanced foundations in statistical methodologies and machine learning.
- Demonstrate strong practical experience with supervised learning methods, gradient boosting, and handling high-cardinality categorical data.
- Show proficiency in exploratory data analysis and creative problem-solving for dataset collection without relying solely on pre-labeled data.
- Exhibit expertise in real-time machine learning service development, including inference integration and building minimum viable product web services.
- Apply excellent coding skills in SQL along with general software engineering tools such as Git, CI/CD pipelines, IDEs, and shell scripting.
- Communicate fluently in English to collaborate effectively within a global and distributed remote team.
Nice to have
- An academic background and a research mindset
- Backend development experience with Go
- Experience with analytical storage systems such as ClickHouse, Snowflake, or BigQuery
- Familiarity with engineering practices for maintaining data transformations using frameworks like dbt
- Hands-on experience with vector databases and embedding-based search systems
Skills and tech stack
Questions candidates ask
What is the remote work policy?
Fingerprint is a globally dispersed, 100% remote company where people can join the workforce from almost any country. Teammates need to be authorized to work from their home location, though there is a small number of countries where the company cannot base teammates due to regulatory and security reasons.
What is the salary range for the role?
For US-based employees, the cash compensation range is $152,000 to $205,000. Offers vary depending on relevant experience, education, certifications, skills, training, and market conditions.
What technologies will I be working with?
The tech stack includes Go, SQL, advanced machine learning frameworks, ClickHouse, dbt, and AWS infrastructure. Engineers also use standard software tools like Git, CI/CD pipelines, and shell scripting.
Does the role involve an on-call schedule?
Yes, the position includes participation in a shared on-call rotation. Schedules are communicated in advance, and the team balances coverage equitably while minimizing off-hours disruption.