Level

Coinbase

Staff Machine Learning Engineer(Platform - Identity)

Coinbase is hiring a Staff Machine Learning Engineer(Platform - Identity) for a remote role open to applicants in United States. It pays $218k-$257k a year and Level rates it ; you can apply on Coinbase.

Level's read on this job

  • On Level's scale, this machine learning engineer role is Builds AI ●●●●: the job is building AI systems.
  • The listed pay starts 9% above the typical machine learning engineer posting on Level.
  • The posting lists this role as remote.
  • Tools and skills the posting cites include PyTorch, TensorFlow and Python.
  • Level lists 226 other open roles at Coinbase.

AI in this role

Own and scale production machine learning systems for identity verification, biometrics, and fraud detection at Coinbase.

pytorchtensorflowpythongnncomputer-vision
computer-visionnlp

Ready to do the most impactful work of your career? At Coinbase, 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.

Staff Machine Learning Engineer, Identity Verification

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:N face-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.

Required Skills and Experience:

  • 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)). 

 

Annual base salary range (excluding equity and bonus):$218,025—$256,500 USD
  • Application Limit: Candidates may submit a maximum of 3 applications within a 6-month period.
  • Equal Opportunity Employer: Coinbase is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or genetic information. Applicants with criminal histories will be considered consistent with applicable federal, state, and local laws.
  • US Applicants: View Employee Rights, Know Your Rights, and E-Verify Notice of Participation.
  • Accommodations: If you are an individual with a disability who needs a reasonable accommodation, email us your request and contact info at accommodations[at]coinbase.com. Need screen reading technology? Click here to download a free compatible screen reader and view the tutorial.
  • Data Privacy & Arbitration: By submitting your application, you agree to our Candidate Privacy Notice. US applicants: By submitting your application, you agree to Arbitration of Disputes.

How we rate this

Staff Machine Learning Engineer(Platform - Identity) at Coinbase rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Computer visionNLPPyTorchTensorFlowPythonGnn

Also common in machine learning engineer jobs at this level

Pay

This job starts at
$218k
Typical machine learning engineer job
$199k

This posting starts 9% above the typical machine learning engineer job. See machine learning engineer jobs

Questions you could be asked

  1. Walk me through a computer vision problem you solved, from raw data to a deployed model.
  2. What NLP problem have you worked on, and how did you measure whether it actually worked?
  3. What are the limits of PyTorch that you've run into, and how did you work around them?
  4. What's a project where you used TensorFlow hands-on?
  5. Walk me through how you've used Python in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Computer vision, NLP, PyTorch, TensorFlow, and Python. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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