Fingerprint is hiring: Senior Machine Learning Engineer in Chicago

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 (20K stars on GitHub).
We have raised $77M and are backed by Craft Ventures, Nexus Venture Partners, and Uncorrelated Ventures. We are seeking a Senior ML Engineer to join our Identification team. In this role, you will focus on designing, building, and maintaining production-grade ML solutions and infrastructure that power our fraud detection solutions.
You will collaborate closely with other team members to architect solutions that are reliable, scalable, and efficient. You will own features from concept to deployment and ensure seamless integration with other components in our platform.
Types of Projects and Impact: Take AI & ML applications from prototype to production, partnering closely with Data Scientists and cross-functional teams to ensure robust and performant deployment of machine learning solutions
Lead development for ML systems: Design, build, and maintain production-grade ML systems, with a focus on performance, scalability, and maintainability
Architect end-to-end ML infrastructure: Own the full lifecycle of ML solutions — from feature engineering and data pipelines to model serving, CI/CD, observability, and retraining
Collaborate across teams: Work closely with data scientists, data engineers, platform teams, and business stakeholders to deliver solutions that align with product and business needs
Champion MLOps best practices: Establish & maintain infrastructure/tooling for versioning, experimentation, testing, deployment, and monitoring of ML models
Enable reproducibility and scale: Develop reusable components, templates, and automation to scale ML development across use cases and teams
This role includes participation in a shared on-call rotation. The schedule will be communicated in advance, and we strive to balance coverage equitably while minimizing off-hours disruptions.
Required Skills: BS/MS in Computer Science, Data Science, or a related field, or equivalent work experience
5+ years of experience as an ML Engineer
Experience establishing and driving best practices for ML/MLOps in a growing technology organization
Strong understanding of core ML concepts including supervised and unsupervised learning, model evaluation, and feature engineering
Hands-on experience with modern ML frameworks such as CatBoost, LightGBM, TensorFlow, or PyTorch, and with large-scale data processing and transformation pipelines for training and serving models
Experience deploying models to cloud platforms such as AWS, GCP, or Azure, using tools like SageMaker, Vertex AI, or Azure ML.
Experience leveraging containerization and orchestration technologies such as Docker and Kubernetes
Experience with CI/CD pipelines and MLOps tooling (e.g., MLflow, Feast, Weights & Biases).
Ability to thrive in ambiguous environments where you get to work directly with stakeholders with minimal guidance and direction
Proficient in English for clear communication in a global, remote team
Nice to Have: Experience working with GoLang or similar languages
Experience working with Vector Databases such as Pinecone, Qdrant or similar technologies
Practical experience with analytical storage systems like ClickHouse, Snowflake, BigQuery, Redshift, or Databricks.
Experience with data transformation frameworks like dbt or other data pipeline tools.
Familiarity with data visualization tools such as Apache Superset, Tableau, or Looker.
Technologies You Will Work With: Backend development: Python, GoLang
ML frameworks: CatBoost, PyTorch
Cloud platforms: AWS
Data analytics/processing: ClickHouse, dbt, Apache Superset.
We are dedicated to creating an inclusive work environment for everyone. We embrace and celebrate the unique experiences, perspectives and cultural backgrounds that each employee brings to our workplace. Fingerprint strives to foster an environment where our employees feel respected, valued and empowered, and our team members are at the forefront in helping us promote and sustain an inclusive workplace.
Fingerprint is an equal opportunities employer and welcomes applications from all qualified candidates. We are committed to providing a positive and inclusive work environment for all employees, regardless of their background, culture, or personal characteristics.

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In Summary: Fingerprint empowers developers to stop online fraud at the source . We work on turning radical new ideas in the fraud detection space into reality . We are seeking a Senior ML Engineer to join our Identification team . In this role, you will focus on designing, building, and maintaining production-grade ML solutions .

En Español:

Fingerprint empodera a los desarrolladores para detener el fraude en línea en la fuente. Trabajamos en convertir nuevas ideas radicales en el espacio de detección del fraude en realidad. Nuestros productos están enfocados al desarrollo y nuestros clientes van desde desarrolladores solos hasta compañías que cotizan en bolsa. Somos una compañía remota 100% dispersada a nivel mundial con un fuerte enfoque en código abierto. Usted poseerá características desde el concepto hasta la implementación y garantizará una integración perfecta con otros componentes en nuestra plataforma. Tipos de proyectos e impacto: Tome las aplicaciones AI & ML del prototipo a la producción, colaborando estrechamente con los científicos de datos y equipos interfuncionales para asegurar un despliegue robusto y eficaz de soluciones de aprendizaje automático Desarrollo principal para sistemas ML: Diseño, construcción y mantenimiento de sistemas ML de nivel productivo, centrándose en el rendimiento, escalabilidad y conservabilidad Arquitecto de infraestructura ML extremo a extremo: Poseer todo el ciclo de vida de las soluciones ML desde ingeniería y tuberías de datos hasta servicio de modelos, CI / CD, observabilidad y reentrenamiento Colaborar entre equipos: Trabajar en estrecha colaboración con científicos de información, ingenieros de datos, equipos de plataformas y partes interesadas empresariales para ofrecer soluciones que se alineen con las mejores prácticas de desarrollo de productos y empresas Campeón EsLOps: Esta función incluye desarrollar y implementar mejor versiones de software ML/fectuales para su uso a gran escala, capacitarse a través de modelos de prueba, monitorización y automatización, así como mantener la capacidad de repetizabilidad en todos los ejemplares de pruebas y procesos de desarrollo; El calendario se comunicará con anticipación, y nos esforzaremos por equilibrar la cobertura de manera equitativa al tiempo que minimizamos las interrupciones fuera del horario. Las habilidades requeridas: BS/MS en Ciencias de la Computación, Ciencia de Datos o un campo relacionado, o experiencia laboral equivalente 5+ años como Ingeniero ML Experiencia estableciendo y dirigiendo mejores prácticas para ML / MLOps en una organización tecnológica en crecimiento comprensión sólida de los conceptos básicos de ML incluido el aprendizaje supervisado y no supervisionado, evaluación de modelos e ingeniería de características Mano a mano con modernos marcos ML tales como CatBoost, LightGBM, PyTorchFlow, y TensorProjección de datos a gran escala para capacitación y transformación de modelos Apache. Acogemos y celebramos las experiencias únicas, perspectivas y antecedentes culturales que cada empleado trae a nuestro lugar de trabajo. Fingerprint se esfuerza por fomentar un entorno en el que nuestros empleados se sientan respetados, valorados y empoderados, y los miembros de nuestro equipo están a la vanguardia para ayudarnos a promover y sostener un ambiente laboral inclusivo.