Machine Learning Engineer | Fraud Detection & AI

🚀 Machine Learning Engineer | Fraud Detection & AI

Location: Remote — US or Canada

Employment Type: Full-time

Salary: $175K–$220K + Competitive Equity

Openings: 3

About the Role

Sardine is looking for a Machine Learning Engineer to build the systems powering real-time fraud detection. You’ll work across applied machine learning, data pipelines, and backend engineering to develop reliable, scalable solutions for high-stakes fraud and security challenges.

What You’ll Do

• Build and optimize real-time data pipelines and backend services

• Develop, deploy, and optimize ML models for fraud detection

• Turn raw device and behavioral data into production-ready features

• Integrate ML models with backend and platform systems

• Build systems capable of serving latency-sensitive predictions at scale

• Maintain strong security, privacy, and compliance standards

• Implement testing, documentation, monitoring, and observability best practices

Required Qualifications

• 5–8 years of software engineering experience

• Strong backend engineering experience with Go or Python

• Hands-on applied ML experience with large datasets

• Experience with PyTorch, Scikit-learn, or similar frameworks

• Strong SQL skills and experience with relational/non-relational databases

• End-to-end ML ownership: feature pipelines, deployment, monitoring, and iteration

• Experience with real-time ML systems serving predictions at scale

• Fraud/security experience such as bot detection, device fingerprinting, VPN/proxy detection, or similar

• BS or MS in Computer Science, Engineering, or a related field

• Excellent written and verbal English communication

• Self-directed and comfortable working with ambiguity

Nice to Have

• Go backend development experience

• CI/CD, Docker, Kubernetes, and modern DevOps experience

• ML platform tooling and drift monitoring

• Browser APIs and high-entropy data collection

• Experience leveraging frontier LLMs for automation

• Background in fraud, risk, cybersecurity, fintech, payments, or trust & safety

Ideal Background

Candidates from companies such as:

Fraud & Risk: Sift, Featurespace, Feedzai, Socure, Riskified, Unit21, Alloy, Vanta, Doppel

Cybersecurity: Palo Alto Networks, CrowdStrike, SentinelOne, Darktrace, Vectra AI

FinTech & Payments: Stripe, Block, PayPal, Plaid, Adyen, Brex, Taktile, Middesk, Flare

Trust & Safety / Applied ML: Google, Meta, Amazon, Apple, Netflix

Remote & Location

Remote-first for candidates based in the US or Canada.

Offices available in:

• Bay Area

• NYC

• Austin

• Toronto

• São Paulo

Visa Sponsorship: Not available

TN: OK

L1/O1: Case-by-case

H-1B: No sponsorship

Tech Stack

Go • Python • SQL • Docker • Kubernetes • PyTorch • Scikit-learn

📩 Interested or know someone who would be a strong fit? Apply or send me a message.

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