Machine Learning Engineer

Location: New York, San Francisco, South Bay Area, Los Angeles

Job Type: Full-time

Salary Range: $175K – $220K

About the Role

As a Machine Learning Engineer, you’ll do more than build models—you’ll design the systems that make fraud detection possible. You’ll work across modeling, data pipelines, and backend systems (Go) to ensure ML models run reliably, efficiently, and at scale.

This is a chance to combine applied ML with large-scale systems engineering, owning end-to-end solutions that tackle high-stakes, ever-evolving challenges.

What You’ll Be Doing

·       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, ensuring they run reliably and efficiently in production.

·       Turn raw data into production-ready features that feed fraud detection systems.

·       Collaborate with platform and backend engineers to integrate models seamlessly.

·       Maintain high standards of security, privacy, and compliance.

·       Champion best practices in testing, documentation, and observability.

What You’ll Need

·       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 communication skills in English, both written and verbal.

·       Bachelor’s or Master’s degree in Computer Science, Engineering, or a related discipline.

Bonus Points

·       Domain knowledge in fraud, risk, or cybersecurity.

·       Familiarity with CI/CD, Docker, Kubernetes, and modern DevOps frameworks.

·       Understanding of modern browser APIs and high-entropy data collection techniques.

·       Familiarity with leveraging frontier LLMs for automation.

Role Details

Salary

·       $175K – $220K

Equity

·       Competitive equity

Remote Work Policy

·       US or Canada-based, remote-first.

·       Offices available in:

o  Bay Area

o  NYC

o  Austin

o  Toronto

o  São Paulo

Visa Sponsorship

·       Visa sponsorship not available.

·       TN: OK

·       L1/O1: Case-by-case

·       No H1-B sponsorship.

Employment Type

·       Full-time

Hiring Count

·       Looking to hire 3 candidates for this role.

Locations

·       New York

·       San Francisco

·       South Bay Area

·       Los Angeles

Tech Stack

·       Go

·       Python

·       SQL

·       Docker

·       Kubernetes

Requirements

Role Requirements

Seniority

Required:

·       5–8 years of experience in software engineering with strong backend and machine learning work.

Work Experience

Required:

·       End-to-end ML model ownership: feature pipelines, model deployment, monitoring, and iteration (not just experimentation).

·       Fraud domain experience (bot detection, device fingerprinting, VPN/proxy detection, etc.).

Nice to Have:

·       Depth in backend software engineering over data science.

Education

Required:

·       BS or MS in Computer Science, Engineering, or a related field.

Hard Skills

Required:

·       Built latency-sensitive ML systems serving real-time predictions at scale.

·       Familiarity with ML platform tooling: feature pipelines, drift monitoring, model iteration cycles.

Nice to Have:

·       Experience with Go for backend services (or demonstrated ability to pick up new languages quickly).

Soft Skills

Required:

·       Self-directed: navigates ambiguity and delivers with minimal hand-holding after onboarding.

Traits to Avoid

Avoid:

·       Not looking for just ML Ops.

·       Pure model-building focus with no production deployment or infrastructure experience.

What to Ask Candidates

1.     What’s your current work authorization status in the US or Canada (e.g., US citizen, Green Card holder, Canadian PR/Citizen)?

2.     When is the soonest you could start?

3.     Do you have any specific experience with bot detection, device fingerprinting, VPN/proxy detection, or similar fraud/security domains? (Optional)

4.     What are your salary expectations?

5.     How actively are you exploring new opportunities?

Ideal Background

Fraud & Risk Detection

·       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

Application

Send us your updated CV/Resume to contact@remotetalents.website with the subject: “Machine Learning Engineer4500”

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