Senior Machine Learning Engineer, CX Intelligence

About the role

This role focuses on enhancing customer support through advanced machine learning and AI. The engineer will be responsible for designing and implementing the core orchestration layer for conversational AI systems, managing state transitions and intent routing across various LLM frameworks. The work involves bridging cutting-edge ML/AI research with practical, customer-facing products, ensuring reliability and measurability.

A key aspect of this position is leading end-to-end execution of complex ML projects. This includes managing priorities, making technical trade-offs, and coordinating with other teams from initial design to final delivery. The engineer will also establish best practices for system design, coding standards, and overall AI/ML development workflows within the team.

Success in this role means not only delivering high-quality ML solutions but also elevating the technical capabilities of the broader team. This involves mentoring other engineers on architectural integrity and modern AI/ML patterns, as well as conducting design reviews to uphold Coinbase's standards for security, scalability, and performance. The ideal candidate ensures responsible use of generative AI to drive measurable improvements.

The competitive salary range for this role is between $135,000 and $225,000, with total compensation potentially including equity, bonus eligibility, and benefits.

Skills that matter here

• Python: This role requires deep proficiency in Python for building production-grade, maintainable, and highly-tested ML services.
• Machine Learning: The position involves extensive experience in machine learning and software engineering to ship production-grade ML services at scale.
• AI: Candidates need hands-on expertise with modern AI architectures, including LLMs and the generative AI ecosystem, to develop conversational systems.
• NLP: Specialized knowledge in NLP is a requirement, indicating its importance for the conversational AI systems being built.
• Deep Learning: Experience with deep learning is necessary, as it is a component of modern AI architectures used in this role.

Who this role suits

• You have a track record of shipping production-grade ML services at scale.
• You are capable of leading complex technical projects from design through delivery, managing dependencies and trade-offs.
• You are adept at translating complex technical concepts for non-technical audiences and presenting ML system architectures.
• You are committed to mentoring others and establishing best practices to raise the technical bar for a team.

From the employer

• Architect and deploy the orchestration layer that manages state transitions, context sharing, and intent routing across vendor and internal LLM frameworks in a distributed conversational environment.
• Build production-grade Python services that bridge advanced ML/AI research with reliable, measurable customer-facing products.
• Lead end-to-end project execution for complex ML initiatives, managing priorities, technical trade-offs, and cross-functional dependencies from design through delivery.
• Establish best practices for system design, coding standards, and AI/ML development workflows across the team.
• Mentor engineers on architectural integrity and modern AI/ML patterns, raising the technical bar for the broader team.
• Conduct design reviews to ensure every feature meets Coinbase's standards for security, scalability, and performance.

• 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 building with modern AI architectures (LLMs, deep learning) and the generative AI ecosystem, including frameworks such as LangGraph, LangSmith, Google ADK, Vertex AI, or AWS Bedrock.
• Deep proficiency in Python with demonstrated ability to write clean, maintainable, highly-tested production code.
• Specialized knowledge in at least one domain: NLP, information retrieval, computer vision, or advanced statistical modeling.
• Proven ability to write technical design documents and present ML system architectures to cross-functional stakeholders, translating complex technical concepts for non-technical audiences.
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.

• Competitive salary range: $135K-$225K.
• Total compensation may also include equity and bonus eligibility and benefits (including medical, dental, and vision).
• Remote-first work environment with quarterly in-person sessions.