Pay
In line with similar jobs
$191K–$225K against $166K–$240K, the middle half of what similar US postings state.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Senior Machine Learning Engineer, CX
Remote - USA
Live, first seen by us 18 days ago- Pay
USD 191,250–225,000/year · BaseExcludes bonus, equity — pay source
Annual base salary range (excluding equity and bonus): $191,250—$225,000 USD Application Limit: Candidates may submit a maximum of 3 applications within a 6-month period.
Read the full posting- 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. As a Senior Machine Learning Engineer on the CX Intelligence Engineering team within Coinbase's Customer Engagement and Experience org, you'll design and build the AI-powered systems that connect our Help Center, chatbots, and agent workflows. This team owns the multi-agent platform powering Coinbase chat, Help Center, and agent tooling surfaces, partnering with Conversation Design, CX, and Engineering teams to deliver secure, compliant, and scalable AI support. You'll drive key CX automation initiatives, including multi-agent framework development, agent assist capabilities, and LLM-powered secure actions that help customers get answers faster while enabling human agents to resolve cases more effectively.
Listed location: Remote - USA
Read the full posting- Employment
- Not stated
What you’ll work on
Full postingArchitect and deploy a multi-agent framework for agent assist and secure LLM actions
Own end-to-end delivery of complex ML projects, including trade-offs and dependencies
Build AI concierge chat and agent copilot experiences to raise automated resolution rates
Develop systems to detect bad actors and adversarial inputs
Set standards for system design, coding and ML evaluation, and mentor engineers
From the employer’s posting
Architect and deploy the multi-agent framework for agent assist, internal SOP execution, and secure LLM-powered actions
Own end-to-end project execution for complex ML initiatives, managing priorities, technical trade-offs, and cross-functional dependencies
Build and optimize AI-driven concierge chat and agent copilot experiences that improve automated resolution rates
Develop systems to detect and manage bad actors and adversarial inputs
Establish best practices for system design, coding standards, and evaluation frameworks for ML/AI systems, mentoring team members
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 17, 202618 days ago
- Recorded sightings
- 35
- 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 18
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
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- AWS
Where the posting names them
- Hands-on expertise with large language models, deep learning architectures, and the generative AI ecosystem (LangGraph, LangSmith, Google ADK, Vertex AI, or AWS Bedrock), with demonstrated ability to build multi-agent or LLM orchestration systems. - Proficiency in Python with the ability to write clean, maintainable, and highly tested production code for ML applications. - Specialized depth in at least one domain: NLP, information retrieval, conversational AI, or advanced statistical modeling, with the ability to ramp quickly on adjacent areas.
- 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 with large language models, deep learning architectures, and the generative AI ecosystem (LangGraph, LangSmith, Google ADK, Vertex AI, or AWS Bedrock), with demonstrated ability to build multi-agent or LLM orchestration systems. - Proficiency in Python with the ability to write clean, maintainable, and highly tested production code for ML applications.
Your next step
Complete your application on www.coinbase.com. The employer’s form will show what is required.
Applying through Greenhouse
- No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
- Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.
Already applied? Track this application
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
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 Senior Machine Learning Engineer on the CX Intelligence Engineering team within Coinbase's Customer Engagement and Experience org, you'll design and build the AI-powered systems that connect our Help Center, chatbots, and agent workflows. This team owns the multi-agent platform powering Coinbase chat, Help Center, and agent tooling surfaces, partnering with Conversation Design, CX, and Engineering teams to deliver secure, compliant, and scalable AI support. You'll drive key CX automation initiatives, including multi-agent framework development, agent assist capabilities, and LLM-powered secure actions that help customers get answers faster while enabling human agents to resolve cases more effectively.
What you'll do:
- Architect and deploy the multi-agent framework for agent assist, internal SOP execution, and secure LLM-powered actions, building scalable systems that handle millions of customer interactions.
- Own end-to-end project execution for complex ML initiatives, managing priorities, technical trade-offs, and cross-functional dependencies from design through production delivery.
- Build and optimize AI-driven concierge chat and agent copilot experiences that improve automated resolution rates and reduce case handling time.
- Develop systems to detect and manage bad actors and adversarial inputs, ensuring the multi-agent platform maintains high confidence and safety at scale.
- Establish best practices for system design, coding standards, and evaluation frameworks for ML/AI systems, mentoring team members on architectural decisions and modern ML development workflows.
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 with large language models, deep learning architectures, and the generative AI ecosystem (LangGraph, LangSmith, Google ADK, Vertex AI, or AWS Bedrock), with demonstrated ability to build multi-agent or LLM orchestration systems.
- Proficiency in Python with the ability to write clean, maintainable, and highly tested production code for ML applications.
- Specialized depth in at least one domain: NLP, information retrieval, conversational AI, or advanced statistical modeling, with the ability to ramp quickly on adjacent areas.
- Proven ability to write technical design documents and communicate complex ML concepts clearly to non-technical stakeholders across product, design, and CX teams.
- Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.
- Demonstrates the ability to responsibly use generative AI tools and copilots (e.g., LibreChat, Gemini, Glean) in daily workflows, continuously learn as tools evolve, and apply human‑in‑the‑loop practices to deliver business‑ready outputs and drive measurable improvements in efficiency, cost, and quality.
#P78698
Pay Transparency Notice: Base salary varies by location (see range below). Total compensation may also include equity and bonus eligibility, and benefits (medical, dental, vision, 401(k)).
Annual base salary range (excluding equity and bonus):
$191,250—$225,000 USD
- 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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- Pay
Annual base salary range (excluding equity and bonus): $191,250—$225,000 USD Application Limit: Candidates may submit a maximum of 3 applications within a 6-month period.
- Location & working pattern
Remote - USA
This passage needs a closer read in the full description.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.