Lead ML Engineer, CX Intelligence (Remote-First)

Coinbase, Inc.; United States; Hybrid; USD 218,000 - 257,000; Full time

Job summary

Coinbase is seeking a Staff Machine Learning Engineer for the CX Intelligence team to lead design and delivery of production ML systems, shaping technical strategy and collaborating with product and engineering to enhance customer experience.

You will drive end-to-end ML projects, mentor engineers, and build scalable pipelines with a focus on safe, high-quality outputs and measurable improvements in workflows.

Qualifications

• 8+ years of experience in machine learning and software engineering.
• Hands-on experience with LLMs, deep learning, graph neural networks, or gradient-boosted trees.
• Strong Python skills and production-grade code for ML services.
• Experience mentoring engineers and leading design reviews across a team.
• Focus on responsible AI with human oversight to improve outcomes.

Responsibilities

• Own the design and delivery of production ML systems using LLMs, deep learning, graph networks and more.
• Partner with leadership to define strategic roadmaps and translate vision into quarterly plans.
• Lead high-impact ML projects end-to-end from architecture to production.
• Build scalable, secure ML systems, evaluation pipelines, and data workflows with well-tested Python code.
• Mentor engineers and establish team-wide design/testing/observability standards.
• Drive security, responsible AI, and architectural reviews to improve reliability and latency.

Skills

Python programming

ML system design

Mentoring engineers

LLMs / Deep Learning

NLP / Information retrieval

Production ML experience

Data pipelines

Job description

Coinbase is seeking a Staff Machine Learning Engineer for the CX Intelligence team to lead design and delivery of production ML systems, shaping technical strategy and collaborating with product and engineering to enhance customer experience.

You will drive end-to-end ML projects, mentor engineers, and build scalable pipelines with a focus on safe, high-quality outputs and measurable improvements in workflows.