Staff Machine Learning Engineer(Platform - Identity)

Coinbase, Inc.
Dover, DE, United States
13 days ago
Apply on dejobs.org
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Compensation
$218,025.0 - $256,500.0
Working hours
Regular working hours
Job source

Tech stack

Computer Vision Biometrics Python (Programming Language) Machine Learning Tensorflow Azure Machine Learning Dynamic Routing Pytorch Large Language Models Machine Learning Operations

Job description

As a Staff Machine Learning Engineer on the Identity Verification team within the Platform group, you’ll own the ML systems that determine whether a person, document, and capture session are legitimate. Every signup, account recovery, and high-risk action at Coinbase depends on these models. You’ll lead the technical strategy for IDV ML end-to-end, from architecture through production enforcement, protecting the integrity of millions of accounts.

What you’ll do:

  • Own the full IDV ML stack, including document authenticity models, 1:1 and 1:Nface-match, liveness detection, presentation-attack detection, and deepfake/injection detection from feature pipeline through threshold tuning and production enforcement.
  • Build identity-graph systems using GNNs that cluster accounts sharing biometric, device, and document signals to detect synthetic-identity rings and coordinated fraud at onboarding.
  • Develop behavioral and device-intelligence models for capture-session anomaly detection, bot-vs-human classification, and device-fingerprint-based risk scoring at real-time latency.
  • Drive vendor ML strategy by benchmarking external models against a Coinbase-owned evaluation set, designing dynamic routing logic across providers and geographies, and building the in-house evaluation layer that catches regressions before they reach users.
  • Lead and mentor senior and mid-level engineers in the pod while partnering with ML Platform and Risk ML teams to align cross-company ML system design.

Requirements

  • 8+ years deploying production ML systems at scale, with proven technical leadership owning cross-team ML architecture from design through production.
  • Domain experience in identity verification, biometrics, or account integrity with deep applied ML in at least two of: computer vision/biometrics, GNNs, sequence models, or NLP/LLMs.
  • Expert-level Python with production experience in TensorFlow or PyTorch, including model training, evaluation, and serving infrastructure.
  • Track record translating KYC/AML requirements and fraud trends into ML roadmaps and communicating trade-offs to Product, Compliance, Risk, and Security stakeholders.
  • Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.

*Pay Transparency Notice:** *Base salary varies by location (see range below). Total compensation may also include equity and bonus eligibility, and benefits (medical, dental, vision, 401(k)).

About the company

Ready to do the most impactful work of your career? AtCoinbase, we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn’t a place for complacency, it’s a place to be pushed past your perceived limits. If you’re ready to build the future of finance alongside people who refuse to settle for “good enough,” you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.”learn more about working at Coinbase.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on dejobs.org
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:30 min

Challenges of automated application screening in recruiting

Kilian Kluge +1 · World Congress 2022

2:35 min

Preventing remote code execution in PyTorch models

Balázs Kiss · World Congress 2023

1:39 min

Fundamentals of tensors and the TensorFlow library

Håkan Silfvernagel · LIVE

1:41 min

Exploring possession and biometric authentication factors

Clemens Hübner Clemens Hübner · World Congress 2023

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

1:02 min

Integrating biometric face liveness for physical identity checks

Alvaro Navarro · World Congress 2024

Videos

See all

Related articles

See all