Machine Learning Engineer (L3)
As a Machine Learning Engineer, you will develop AI/ML capabilities to enhance customer engagement experiences, ensuring seamless interactions across applications and channels.
Ready to do the most impactful work of your career? At Coinbase, we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, itโs a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called โsurges.โ learn more about working at Coinbase.
The CX Intelligence Engineering team, part of Coinbase's Enterprise Applications and Architecture org, builds the multi-agent platform powering Coinbase Chat, Help Center, and agent tooling. As a Machine Learning Engineer on this team, you'll design and scale the agentic systems that automate complex customer support workflows, connecting LLMs with internal APIs and tools to deliver fast, accurate, and compliant AI-powered experiences for millions of customers.
What you'll do:
Required Skills and Experience:
Job ID: P77545
Pay Transparency Notice: The target annual base salary for this position can range as detailed below. Total compensation may also include equity and bonus eligibility and benefits (including medical, dental, and vision).
As a Machine Learning Engineer, you will develop AI/ML capabilities to enhance customer engagement experiences, ensuring seamless interactions across applications and channels.
Build and scale machine learning infrastructure, models, and AI platforms, with a focus on voice and speech use cases, enabling product teams to deliver reliable, customer-facing AI features.
Build, operate, and improve production ML/AI services by combining Python software engineering, container orchestration, CI/CD, and model lifecycle practices to deliver secure, reliable, and maintainable solutions.
Build and deploy production-grade machine learning systems for client challenges, shaping scalable software architecture and deployment standards while advising stakeholders and collaborating across technical and commercial teams.
Build and improve a live AI therapist delivering evidence-based CBT by developing safe, natural voice sessions, rigorous evaluations, and outcome modelling in collaboration with clinicians.