Machine Learning Engineer

Stack

Responsibilities

• ▹Build and optimize data pipelines and backend services to process device and behavioral data in real time
• ▹Develop and deploy ML models for fraud detection, running reliably and efficiently in production
• ▹Turn raw data into production-ready features for fraud detection systems
• ▹Collaborate with platform and backend engineers to integrate models
• ▹Maintain high standards of security, privacy and compliance
• ▹Champion best practices in testing, documentation and observability

Requirements

• ▹5+ years in software engineering, with strong backend experience (Go or Python)
• ▹Hands-on experience with applied ML using large datasets (PyTorch, Scikit-learn, etc.)
• ▹Strong SQL skills and familiarity with relational and non-relational databases
• ▹Experience with end-to-end ML systems: feature pipelines, model deployment, monitoring and iteration
• ▹Excellent written and verbal English communication
• ▹Bachelor's or Master's in Computer Science, Engineering or a related discipline
• ▹Based in the United States or Canada (remote)

Nice to have

• ▹Domain knowledge in fraud, risk or cybersecurity
• ▹Familiarity with CI/CD, Docker, Kubernetes and modern devops
• ▹Understanding of modern browser APIs and high-entropy data collection techniques
• ▹Familiarity with leveraging frontier LLMs for automation

Soft skills

What we offer

• ▹Generous compensation in cash and equity
• ▹Early exercise for all options, including pre-vested
• ▹Work from anywhere, remote-first culture
• ▹Flexible paid time off and year-end break
• ▹Health, dental and vision coverage for employees and dependents (US and Canada)
• ▹4% matching in 401k / RRSP (US and Canada)
• ▹MacBook Pro delivered to your door
• ▹One-time home office stipend
• ▹Monthly meal and social meet-up stipends
• ▹Annual health and wellness and learning stipends

About the company

Sardine is the leading agentic risk platform for fighting financial crime, stopping fraud in real time. It has hubs in the Bay Area, NYC, Austin, Toronto and São Paulo, and a remote-first culture.