Machine Learning Engineer

About the role

This role focuses on developing AI-driven customer support tools, specifically working with large language models (LLMs). The engineer will build and refine the orchestration layer that manages how these AI systems handle conversations, share context, and route user intentions. This involves creating robust Python services that integrate advanced AI and machine learning features into customer-facing products.

The position requires taking ML projects from initial design to final delivery, making technical decisions, and working with various teams. A key part of the job is ensuring that the developed systems meet Coinbase's standards for security, compliance, and performance. This includes contributing to system design, coding standards, and best practices for AI/ML development.

Success in this role means building secure, scalable, and high-performing AI-enabled experiences. The ideal candidate will partner with other engineers and stakeholders to achieve this, using generative AI responsibly to deliver business-ready outputs. This work directly contributes to improving efficiency, reducing costs, and enhancing the quality of customer support.

The competitive salary for this role ranges from $120,000 to $200,000 annually, with potential for additional equity and bonus eligibility.

Skills that matter here

• machine learning: This role requires applying machine learning principles to build and deploy AI-powered customer support solutions.
• python: Proficiency in Python is essential for developing production-grade services and writing clean, maintainable code.
• AI: The position involves working with modern AI architectures, including LLMs, to create conversational environments.
• deep learning: Experience with deep learning is necessary for implementing advanced AI capabilities within the customer support systems.
• NLP: Working knowledge of natural language processing is required for handling and interpreting conversational data.

Who this role suits

• A candidate who has at least two years of professional experience in both machine learning and software engineering.
• Someone with practical experience in modern AI architectures like LLMs and deep learning, including tools such as LangGraph or Vertex AI.
• An individual who can clearly communicate complex ML system designs and technical trade-offs to various stakeholders.
• A person who uses generative AI responsibly, ensuring human oversight and measurable improvements in business outcomes.

From the employer

• Build and improve the orchestration layer that manages state transitions, context sharing, and intent routing across vendor and internal LLM frameworks in a distributed conversational environment.
• Develop production-grade Python services that bridge advanced AI and ML capabilities with reliable customer-facing products.
• Drive well-scoped ML projects from design through delivery, balancing technical trade-offs and collaborating across teams.
• Contribute to system design, coding standards, and AI/ML development best practices across the team.
• Partner with engineers and cross-functional stakeholders to build secure, scalable, and high-performing AI-enabled experiences.
• Participate in design reviews and help ensure features meet Coinbase standards for security, compliance, and performance.

• 2+ years of professional experience in machine learning and software engineering, with experience shipping production-grade ML services.
• Hands-on experience building with modern AI architectures such as LLMs and deep learning, and familiarity with tools such as LangGraph, LangSmith, Google ADK, Vertex AI, or AWS Bedrock.
• Strong proficiency in Python and the ability to write clean, maintainable, well-tested production code.
• Working knowledge in at least one domain such as NLP, information retrieval, computer vision, or statistical modeling.
• Ability to write technical design documents and communicate ML system designs clearly to cross-functional stakeholders.
• Uses generative AI responsibly, applying human oversight to deliver business-ready outputs and measurable improvements in efficiency, cost, and quality.

• Competitive salary ranging from $120K to $200K.
• Total compensation may also include equity and bonus eligibility and benefits (including medical, dental, and vision).
• Remote-first work environment with quarterly in-person working sessions.