Machine Learning Engineer focused on building sophisticated AI/ML models to protect Coinbase users from fraud. Collaborating on risk detection systems for an innovative financial platform.
Responsibilities
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.
Requirements
8-10+ 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 leading small teams or pods and designing and deploying large-scale, cross-team ML systems from scratch.
Passion & Values: A commitment to building an open financial system and a strong desire to protect users from fraud and scams. You embody our core cultural values: add positive energy, communicate clearly, be curious, and be a builder.
AI/ML Knowledge: Deep expertise in applied AI/ML techniques (e.g., Risk ML, deep learning, NLP, recommender systems, anomaly detection); with required prior domain experience in Payment Risk, Credit Risk, or Identity Risk / Account Takeover / Scams.
Technical & Coding Skills: Expert-level coding skills (e.g., Python) and deep experience with AI/ML frameworks (TensorFlow, PyTorch). Experience in building backend systems with a focus on data processing or analytics is a plus.
Team Collaboration: Ability to work collaboratively on technical initiatives and contribute to impactful AI/ML solutions.
Communication Skills: Strong communication skills, with the ability to convey technical concepts to both technical and non-technical audiences.
Senior Machine Learning Engineer at Itaú, driving innovation with data and AI solutions. Collaborating across teams to implement robust machine learning architectures and ensure scalable deployments.
Machine Learning Engineer responsible for developing and deploying advanced ML and AI solutions at Zendesk. Collaborating with stakeholders to deliver impactful business outcomes using latest machine learning technologies.
Lead advanced machine learning model development and optimization at PayPal. Collaborate with teams to deploy scalable ML solutions in production environments.
Senior Machine Learning Engineer at Pivotal Health developing ML systems for healthcare reimbursement. Collaborating across teams to build and maintain reliable, production - grade machine learning systems.
Machine Learning Engineer working with Algorithm team on customer onboarding processes. Focus on execution and automation of models using computer vision and AI in sports industry.
Senior Machine Learning Engineer at Troveo designing and optimizing machine learning pipelines for AI video models. Collaborating with cross - functional teams to build scalable video data solutions.
Software Engineer focusing on ML infrastructure for drug discovery at Genesis AI. Leading engineering efforts to enhance scalable platforms for generative modeling and large - scale simulations.
AI/ML Engineer developing machine learning systems for TymeX's digital banking platform. Collaborating across teams to enhance customer interaction and personalization through AI technology.