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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. As a Machine Learning Engineer on the CX Intelligence team within Enterprise Applications and Architecture, you'll build the AI-powered conversational systems that connect Coinbase's Help Center, chatbots, and agent workflows. The team owns the multi-agent platform powering Coinbase Chat and agent tooling, partnering with Conversation Design, CX, and Engineering to deliver secure, scalable automated support. You'll lead the design and implementation of a unified orchestration layer that coordinates interactions between vendor AI, internal multi-agent systems, and human participants, directly improving how millions of customers get help. What you'll do: 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. Build production-grade Python services that bridge advanced ML/AI research with reliable, measurable customer-facing products. Lead end-to-end project execution for complex ML initiatives, managing priorities, technical trade-offs, and cross-functional dependencies from design through delivery. Establish best practices for system design, coding standards, and AI/ML development workflows across the team. Mentor engineers on architectural integrity and modern AI/ML patterns, raising the technical bar for the broader team. Conduct design reviews to ensure every feature meets Coinbase's standards for security, scalability, and performance. Required Skills and Experience: 5+ years of professional experience in machine learning and software engineering, with a track record of shipping production-grade ML services at scale. 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. Deep proficiency in Python with demonstrated ability to write clean, maintainable, highly-tested production code. Specialized knowledge in at least one domain: NLP, information retrieval, computer vision, or advanced statistical modeling. Proven ability to write technical design documents and present ML system architectures to cross-functional stakeholders, translating complex technical concepts for non-technical audiences. 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: 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). Annual base salary range (excluding equity and bonus):: R$455.500 BRL - R$455.500 BRL Application Limit: Candidates may submit a maximum of 4 applications per 30-day 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. 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 is also piloting an AI interview intelligence platform to transcribe and summarize interview notes, allowing our interviewers to fully focus on you as the candidate. Coinbase will not use AI to make decisions impacting employment.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.