Coinbase

Machine Learning Engineer, CX Intelligence

Remote - Brazil

Open 4 months, first seen by us 120 days ago

Pay: Multiple pay amounts — pay source
Annual base salary range (excluding equity and bonus): R$347.900—R$347.900 BRL Application Limit: Candidates may submit a maximum of 3 applications within a 6-month period.
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Work setting: Working pattern needs review — work setting source
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. The CX Intelligence Engineering team, part of Coinbase's Enterprise Applications and Architecture org, builds the multi-agent platform powering Coinbase Chat, Help Center, and agent tooling. As a Machine Learning Engineer on this team, you'll design and scale the agentic systems that automate complex customer support workflows, connecting LLMs with internal APIs and tools to deliver fast, accurate, and compliant AI-powered experiences for millions of customers.
Listed location: Remote - Brazil
Read the full posting
Employment: Not stated

What you’ll work on

Full posting

Architect multi-agent systems with LangGraph or Google ADK to automate support procedures end-to-end
Build Model Context Protocol integrations connecting LLMs to internal APIs, databases and tools
Develop LLM-as-a-judge pipelines to monitor and improve production AI agents
Apply RAG, fine-tuning and prompt engineering so chatbot answers are grounded and policy-compliant
Ship resilient, low-latency Python microservices that handle high traffic

From the employer’s posting

Architect multi-agent systems using advanced orchestration frameworks (LangGraph, Google ADK) to automate complex customer support procedures end-to-end.

Build and scale integrations using Model Context Protocol (MCP) to connect LLMs with internal Coinbase APIs, databases, and third-party tooling.

Develop automated "LLM-as-a-judge" evaluation pipelines to monitor, measure, and improve the performance of non-deterministic AI agents in production.

Implement RAG, fine-tuning, and prompt engineering techniques to ensure chatbot responses are grounded, accurate, and compliant with Coinbase policies.

Ship production-ready Python services that are resilient, low-latency, and capable of handling Coinbase-scale traffic across asynchronous microservices.

Apply at Coinbase

Posting record

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Open 4 monthsWe first saw this posting 120 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records: Live
First seen by us: Jul 7, 2026120 days ago
Recorded sightings: 172
Last seen by us: Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 120

Up longer than most. Similar jobs usually come down between day 6 and day 69.

From 4,347 similar postings that came down. Coming down is not always a hire.

Coinbase is hiring

25 open jobs

Open jobs by the week we first saw them, last 12 weeks.

ML Engineer hiring is picking up
Takes jobs down at a usual pace

Hiring record

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Python

Where the posting names them

- Implement RAG, fine-tuning, and prompt engineering techniques to ensure chatbot responses are grounded, accurate, and compliant with Coinbase policies. - Ship production-ready Python services that are resilient, low-latency, and capable of handling Coinbase-scale traffic across asynchronous microservices. - Partner with Conversation Design and Product to translate complex business logic into executable agent procedures within the decentralized architecture.

- Deep understanding of the LLM lifecycle including context window management, token optimization, structured output parsing (Pydantic, JSON mode), and multi-agent orchestration frameworks (LangGraph, Google ADK, or similar). - Strong proficiency in Python with hands-on experience in microservices architecture, asynchronous programming, high-throughput APIs, and vector databases (Pinecone, Weaviate, or equivalent). - Demonstrated ability to explain model behaviors and technical trade-offs to non-technical stakeholders across CX, Legal, and Product teams.

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025: $140,300
Expected change, 2025 to 2035: 21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

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.

The CX Intelligence Engineering team, part of Coinbase's Enterprise Applications and Architecture org, builds the multi-agent platform powering Coinbase Chat, Help Center, and agent tooling. As a Machine Learning Engineer on this team, you'll design and scale the agentic systems that automate complex customer support workflows, connecting LLMs with internal APIs and tools to deliver fast, accurate, and compliant AI-powered experiences for millions of customers.

What you'll do:

Architect multi-agent systems using advanced orchestration frameworks (LangGraph, Google ADK) to automate complex customer support procedures end-to-end.
Build and scale integrations using Model Context Protocol (MCP) to connect LLMs with internal Coinbase APIs, databases, and third-party tooling.
Develop automated "LLM-as-a-judge" evaluation pipelines to monitor, measure, and improve the performance of non-deterministic AI agents in production.
Implement RAG, fine-tuning, and prompt engineering techniques to ensure chatbot responses are grounded, accurate, and compliant with Coinbase policies.
Ship production-ready Python services that are resilient, low-latency, and capable of handling Coinbase-scale traffic across asynchronous microservices.
Partner with Conversation Design and Product to translate complex business logic into executable agent procedures within the decentralized architecture.

Required Skills and Experience:

3+ years building and scaling ML/AI systems in production, with demonstrated experience implementing agentic "Loop" or "ReAct" based systems where AI takes actions autonomously.
Deep understanding of the LLM lifecycle including context window management, token optimization, structured output parsing (Pydantic, JSON mode), and multi-agent orchestration frameworks (LangGraph, Google ADK, or similar).
Strong proficiency in Python with hands-on experience in microservices architecture, asynchronous programming, high-throughput APIs, and vector databases (Pinecone, Weaviate, or equivalent).
Demonstrated ability to explain model behaviors and technical trade-offs to non-technical stakeholders across CX, Legal, and Product teams.
Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.

Job ID: P77545

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$347.900—R$347.900 BRL

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.

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