Staff Machine Learning Engineer, Platform - Identity

Coinbase

Confirmed live 2 days ago High trust
Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$218,025–$256,500 / yr
Posted
8 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $232k
This role $237k
$174k most similar roles pay here $289k

This role pays less than 52% of similar roles. Most pay $208,575–$254,750 — the shaded band above. At the midpoint, this role pays about $237k versus about $232k for comparable roles.

Based on 240 similar postings.

Employer

About Coinbase

Coinbase Global is a publicly traded cryptocurrency exchange platform where consumers can buy, sell, and store digital currencies including Bitcoin, Ethereum, and hundreds of other cryptocurrencies. Industry: Cryptocurrency Exchange & Financial Technology

Coinbase currently has 62 open roles on FindRole.

Listed pay typically runs $201,790–$237,400 across 54 roles with salary data.

Most-posted roles

View all roles at Coinbase

At a glance

TL;DR · Staff Machine Learning Engineer, Platform - Identity

As a Staff Machine Learning Engineer on the Identity Verification team within the Platform group, you will own the machine learning systems that determine if people, documents, and capture sessions are legitimate. You will manage the full identity verification stack, including document authenticity models, face-match, liveness detection, and deepfake detection. Your work involves building identity-graph systems using GNNs to detect synthetic-identity rings, developing behavioral and device-intelligence models for real-time risk scoring, and driving vendor ML strategy through benchmarking and dynamic routing. You will lead and mentor engineers while translating KYC/AML requirements into technical roadmaps. The role requires expert Python skills with experience in TensorFlow or PyTorch, along with expertise in computer vision, biometrics, sequence models, or NLP/LLMs to solve critical account integrity and fraud detection problems during the onboarding process.

What does a Machine Learning Engineer earn in Remote?

Median $235875 from 52 postings across 19 companies.

See salary data

What you'll do

  • Own the full IDV ML stack including document authenticity, face-match, liveness detection, and deepfake detection.
  • Build identity-graph systems using GNNs to detect synthetic-identity rings and coordinated fraud at onboarding.
  • Develop behavioral and device-intelligence models for real-time anomaly detection and bot-vs-human classification.
  • Drive vendor ML strategy by benchmarking external models and designing dynamic routing logic across providers.
  • Build an in-house evaluation layer to identify model regressions before they reach users.
  • Lead and mentor engineers while aligning cross-company ML system designs with Platform and Risk teams.
  • Translate KYC/AML requirements and fraud trends into actionable machine learning roadmaps for stakeholders.

What we're looking for

  • 8+ years of experience deploying production ML systems at scale with proven technical leadership in cross-team architecture.
  • Domain experience in identity verification, biometrics, or account integrity.
  • Deep applied ML expertise in at least two areas: computer vision/biometrics, GNNs, sequence models, or NLP/LLMs.
  • Expert-level Python skills with production experience in TensorFlow or PyTorch for training, evaluation, and serving.
  • Proven ability to translate KYC/AML requirements and fraud trends into technical ML roadmaps.
  • Experience communicating technical trade-offs to Product, Compliance, Risk, and Security stakeholders.
  • Ability to use generative AI responsibly to improve workflow efficiency, cost, and quality.

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