Senior Machine Learning Engineer, CX Intelligence
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Overview
Join Coinbase as a Senior Machine Learning Engineer to build AI-powered conversational systems and improve customer support. Remote position for LATAM candidates. 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, itβs 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 βsurges.β
What you'll do
- β’Architect and deploy the orchestration layer that manages state transitions, context sharing, and intent routing across vendor and internal LLM frameworks in a distributed conversational environment.
- β’Build production-grade Python services that bridge advanced ML/AI research with reliable, measurable customer-facing products.
- β’Lead end-to-end project execution for complex ML initiatives, managing priorities, technical trade-offs, and cross-functional dependencies from design through delivery.
- β’Establish best practices for system design, coding standards, and AI/ML development workflows across the team.
- β’Mentor engineers on architectural integrity and modern AI/ML patterns, raising the technical bar for the broader team.
- β’Conduct design reviews to ensure every feature meets Coinbase's standards for security, scalability, and performance.
Pay Transparency Notice
- β’The target annual base salary for this position can range as detailed below. Total compensation may also include equity and bonus eligibility and benefits (including medical, dental, and vision).
- β’Annual base salary range (excluding equity and bonus): R$455.500βR$455.500 BRL.
- β’Application Limit: Candidates may submit a maximum of 4 applications per 30-day period.
- β’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.
- β’US Applicants: View Employee Rights, Know Your Rights, and E-Verify Notice of Participation.
- β’Accommodations: If you are an individual with a disability who needs a reasonable accommodation, email us your request and contact info at [email protected]. Need screen reading technology? Click here to download a free compatible screen reader and view the tutorial.
- β’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.
- β’AI Disclosure: Coinbase is piloting an AI tool based on machine learning technologies to conduct initial screening interviews to qualified applicants. The tool simulates realistic interview scenarios and engages in dynamic conversation. Coinbase will not use AI to make decisions impacting employment.
Required Skills and Experience
- β’5+ years of professional experience in machine learning and software engineering, with a track record of shipping production-grade ML services at scale.
- β’Hands-on expertise building with modern AI architectures (LLMs, deep learning) and the generative AI ecosystem, including frameworks such as LangGraph, LangSmith, Google ADK, Vertex AI, or AWS Bedrock.
- β’Deep proficiency in Python with demonstrated ability to write clean, maintainable, highly-tested production code.
- β’Specialized knowledge in at least one domain: NLP, information retrieval, computer vision, or advanced statistical modeling.
- β’Proven ability to write technical design documents and present ML system architectures to cross-functional stakeholders, translating complex technical concepts for non-technical audiences.
- β’Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.