Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 6
Customer Support
Deep Learning @ 7
GenAI
Generative AI @ 6
LLM
Machine Learning @ 4
Mentoring @ 4
NLP
Observability
Python @ 7
Security
Statistics @ 7
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Coinbase is a remote-first, but not remote-only company. Employees are expected to meet quarterly for in-person working sessions called “surges.”
CEE Intelligence (CEEI) is the machine learning and intelligence layer for Coinbase’s customer engagement ecosystem. It builds customer intelligence, evaluation systems, routing and classification models, safety guardrails, and decisioning capabilities that power the Help Center, chat, voice, agent tooling, and other customer support runtimes.
As a Staff Machine Learning Engineer, you will lead the design and delivery of production machine learning systems, shape technical strategy, build scalable intelligence capabilities, and partner with product and engineering stakeholders to improve resolution quality, automation coverage, safety, and customer experience.
Responsibilities
- Own the design and delivery of production machine learning systems using LLMs, deep learning, graph neural networks, and classical machine learning techniques to solve complex customer experience problems.
- Partner with leadership and cross-functional stakeholders to define strategic roadmaps and translate vision into quarterly execution plans with measurable outcomes.
- Lead high-impact machine learning projects end-to-end, from architecture through production, while managing priorities, risks, and dependencies.
- Build scalable, secure, and reliable machine learning systems, evaluation pipelines, and data workflows using high-quality, well-tested Python code.
- Mentor engineers and establish team-wide standards for design, testing, observability, and operational excellence.
- Drive design reviews covering security, responsible AI, model quality, and architectural integrity.
- Improve reliability, scalability, and latency across the technology stack.
Requirements
- 8+ years of experience in machine learning and software engineering, with proven success building, scaling, and maintaining production machine learning systems, data platforms, or analytical services.
- Hands-on expertise with one or more of the following: LLMs, deep learning, graph neural networks, gradient-boosted trees, or regression.
- Strong knowledge of natural language processing, information retrieval, data mining, or advanced statistics.
- Strong Python skills and the ability to write maintainable, highly tested production code for machine learning services.
- Experience mentoring engineers and raising technical standards across a team or organization.
- Experience leading design reviews and influencing technical and non-technical stakeholders.
- Ability to use generative AI responsibly, maintain human oversight, and deliver business-ready outputs that improve workflow efficiency, cost, and quality.
Compensation
Annual base salary ranges from $218,025 to $256,500 USD, excluding equity and bonus. Total compensation may also include equity, bonus eligibility, and medical, dental, vision, and 401(k) benefits.
Job #: P77568