Senior Machine Learning Engineer

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September 29

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Fingerprint

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Cybersecurity • API • SaaS

Fingerprint is a technology company focused on bot detection and identification solutions. The platform helps businesses ensure a secure online environment by accurately identifying users and distinguishing between real users and automated bots. They provide developer guides and workspace settings for easy integration into various applications, enhancing security and user experience.

51 - 200 employees

Founded 2019

🔒 Cybersecurity

🔌 API

☁️ SaaS

💰 $32M Series B on 2021-11

📋 Description

• Design, build, and maintain production-grade ML solutions and infrastructure that power fraud detection • Take AI & ML applications from prototype to production, partnering closely with data scientists and cross-functional teams • Architect end-to-end ML infrastructure: feature engineering, data pipelines, model serving, CI/CD, observability, and retraining • Lead development for ML systems with focus on performance, scalability, and maintainability • Collaborate across teams (data scientists, data engineers, platform teams, business stakeholders) to align solutions with product needs • Champion MLOps best practices: versioning, experimentation, testing, deployment, and monitoring of ML models • Develop reusable components, templates, and automation to scale ML development • Own features from concept to deployment and ensure seamless integration with platform components • Participate in a shared on-call rotation

🎯 Requirements

• 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 • 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 with minimal guidance • Proficient in English for clear communication in a global, remote team • Must be authorized to work from their home location (Fingerprint does not sponsor visas)

🏖️ Benefits

• 100% remote company (globally dispersed) • Strong open-source focus (FingerprintJS) • Inclusive work environment that encourages people from underrepresented groups in tech