Senior Machine Learning Engineer
Fingerprint
full-time
Posted on:
Location Type: Remote
Location: Remote • 🌎 Anywhere in the World
Visit company websiteJob Level
Senior
Tech Stack
AWSAzureCloudDockerGoogle Cloud PlatformKubernetesPyTorchTensorflow
About the role
- 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
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learningMLOpsfeature engineeringdata pipelinesmodel servingCI/CDmodel evaluationsupervised learningunsupervised learningautomation
Soft skills
collaborationleadershipproblem-solvingcommunicationadaptability
Certifications
BS in Computer ScienceMS in Data Science