Staff ML Engineer - CX Intelligence (Remote)

Coinbase, Inc.; Montpelier (VT); Hybrid; USD 218,000 - 257,000; Full time

Job summary

Coinbase, Inc. is seeking a Staff Machine Learning Engineer to lead the design and delivery of production ML systems powering customer engagement.

You will shape technical strategy, collaborate with product and engineering teams, and drive measurable improvements in resolution quality, automation, safety, and CX. You will mentor engineers, define standards for testing, observability, and reliability, and ensure responsible AI with human oversight.

Qualifications

• 8+ years of proven experience building production ML systems.
• Strong knowledge of NLP, IR, data mining, statistics; experience with LLMs or DL.
• Proven ability to write maintainable, tested production ML code in Python.
• Experience mentoring engineers and leading design reviews across teams.
• Commitment to responsible AI with human oversight and safe, scalable systems.

Responsibilities

• Own the design and delivery of production ML systems using LLMs and ML techniques.
• Partner with leadership to translate vision into quarterly execution plans with measurable outcomes.
• Lead high-impact ML projects end-to-end from architecture to production.
• Build secure, scalable ML pipelines and data workflows with quality code.
• Mentor engineers and set engineering standards for testing, observability, and reliability.
• Drive reviews on security, model quality, and architectural integrity across the stack.

Skills

8+ years ML & software

LLMs & DL

Python production code

Mentoring engineers

Responsible AI

Tools

Python

Job description

Coinbase, Inc. is seeking a Staff Machine Learning Engineer to lead the design and delivery of production ML systems powering customer engagement.

You will shape technical strategy, collaborate with product and engineering teams, and drive measurable improvements in resolution quality, automation, safety, and CX. You will mentor engineers, define standards for testing, observability, and reliability, and ensure responsible AI with human oversight.