Staff Machine Learning Engineer - Risk AI/ML

Confirmed live in the last 24 hours

Coinbase

Compensation

$218,025 - $256,500/year

Remote - USA

Remote

Posted January 30, 2026

Job Description

Ready to be pushed beyond what you think you’re capable of?

At Coinbase, our mission is to increase economic freedom in the world. It’s a massive, ambitious opportunity that demands the best of us, every day, as we build the emerging onchain platform — and with it, the future global financial system.

To achieve our mission, we’re seeking a very specific candidate. We want someone who is passionate about our mission and who believes in the power of crypto and blockchain technology to update the financial system. We want someone who is eager to leave their mark on the world, who relishes the pressure and privilege of working with high caliber colleagues, and who actively seeks feedback to keep leveling up. We want someone who will run towards, not away from, solving the company’s hardest problems.

Our work culture is intense and isn’t for everyone. But if you want to build the future alongside others who excel in their disciplines and expect the same from you, there’s no better place to be.

While many roles at Coinbase are remote-first, we are not remote-only. In-person participation is required throughout the year. Team and company-wide offsites are held multiple times annually to foster collaboration, connection, and alignment. Attendance is expected and fully supported.

About the Team
The Risk AI/ML team has a critical mission to foster business growth by effectively managing the financial threats impacting the business and our users. We are on the front lines, building the flexible, scalable, and intelligent systems required to detect and prevent fraud, scams, and account takeovers at scale. As a member of this team, you will build and deploy the sophisticated AI/ML models that power our real-time, near-real-time, and scheduled risk-detection workflows. You will collaborate closely with Platform, Product, Analyst, and Ops teams to uncover new fraud patterns, fight baddies, and continuously improve our defensive capabilities, protecting our good users and the open financial system.

About the Role

We are looking for a Staff Machine Learning Engineer to join our Risk AI/ML team. We are dedicated to building the sophisticated models that protect our customers and make Coinbase the most trusted platform in crypto. Your work will directly prevent fraud, account takeovers, and scams, while enabling future products like instant guest checkout and Coinbase Cards. This is a hands-on technical role where you will leverage our cutting-edge, self-service ML platform to rapidly design, deploy, and iterate on the models that defend millions of users.

What you’ll be doing:

Own a Critical Risk Domain: Take full technical ownership of a core problem space, such as Scams or Account Takeover. You will design, build, and lead the strategy for all models in this domain.
Architect and Design Systems: Lead the system design and architecture for new, complex, cross-team risk detection models. This includes everything from feature pipeline design to model selection (e.g., GNNs, LSTMs, LLMs) and high-performance serving.
Drive the Technical Roadmap: You will be the primary technical voice influencing at an organizational level. Work with Product, Ops, and other stakeholders to translate ambiguous business needs into a clear technical roadmap. You will be the primary technical voice defining the "how."
Mentor and Lead: Act as a senior technical leader and mentor for other senior (IC5), mid-level, and junior engineers on the team.
Apply Advanced ML: Apply modern methodologies (e.g., deep learning, NLP, Graph Neural Networks (GNNs), sequence modeling, and LLMs for NLP and conversational agents) to solve complex, crypto-native challenges.
Build Context-Aware Risk Systems: Architect the adaptive logic that decides which friction (a quiz, an LLM agent, a human review) to apply to which user, balancing security with user experience.

What we look for:

8+ years of professional experience in software engineering and/or AI/ML, with experience deploying AI/ML systems into production.
Proven track record of technical leadership, including l

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