Senior Machine Learning Engineer

About Us

At Coinbase, our mission is to increase economic freedom in the world. It's a massive, ambitious opportunity that demands the best of us, every day, as we build the emerging onchain platform — and with it, the future global financial system.

To achieve our mission, we're seeking a very specific candidate. We want someone who is passionate about our mission and who believes in the power of crypto and blockchain technology to update the financial system. We want someone who is eager to leave their mark on the world, who relishes the pressure and privilege of working with high caliber colleagues, and who actively seeks feedback to keep leveling up. We want someone who will run towards, not away from, solving the company's hardest problems.

Our work culture is intense and isn't for everyone. But if you want to build the future alongside others who excel in their disciplines and expect the same from you, there's no better place to be.

While many roles at Coinbase are remote-first, we are not remote-only. In-person participation is required throughout the year. Team and company-wide offsites are held multiple times annually to foster collaboration, connection, and alignment. Attendance is expected and fully supported.

About the Team

The CX AI Engineering team builds the customer-facing and internal experiences that power our Help Center, AI-powered chatbots, and agent workflows. Our team owns the multi-agent platform at the heart of Coinbase's support ecosystem, partnering closely with Conversation Design, CX Operations, and other Engineering teams to deliver secure, compliant, and scalable AI-driven support.

Our mission is simple: to help customers get accurate answers faster while giving human agents the tools to resolve complex cases more effectively.

The Role

We're looking for a Senior Machine Learning Engineer to drive key CX automation initiatives that directly impact millions of Coinbase customers and thousands of support interactions daily. You will design and build core components of our multi-agent framework — the system that orchestrates LLM-powered agent assist, automated customer conversations, and secure internal workflow execution.

Responsibilities

• Design and build intelligent copilot experiences that help human agents resolve cases faster, and improve our AI-driven concierge chat to handle more customer inquiries end-to-end with high confidence.
• Develop systems to detect and handle bad actors, protecting both customers and agents.
• Own key components of our multi-agent framework from design through production — spanning prompt orchestration, tool integration, and safety guardrails.
• Develop robust, well-tested Python applications with a focus on reliability, latency, and safety. Proactively identify and resolve technical bottlenecks to improve system performance at scale.
• Contribute to best practices for system design, coding standards, and evaluation frameworks. Support the growth of fellow engineers through code reviews, pairing, and knowledge sharing.
• Partner with Product, CX, and Security stakeholders through design reviews and ongoing collaboration to ensure features meet high standards for safety, scalability, and performance.

Requirements

• 5+ years of professional experience in machine learning and software engineering, with a track record of shipping production-grade ML services.
• Hands-on expertise with large language models and deep learning, along with strong Python engineering skills. You care about production reliability as much as model performance.
• Experience with the modern generative AI ecosystem (e.g., LangGraph, LangSmith, Google Vertex AI, AWS Bedrock, or similar). You should be deeply fluent in at least one and able to ramp quickly on others.
• Specialised depth in at least one of the following: NLP, information retrieval, conversational AI, or advanced statistical modeling.
• Strong communication skills. You can explain complex technical concepts clearly to both technical and non-technical audiences.
• Demonstrates the ability to responsibly use generative AI tools and copilots (e.g., LibreChat, Gemini, Glean) in daily workflows, continuously learn as tools evolve, and apply human-in-the-loop practices to deliver business-ready outputs and drive measurable improvements in efficiency, cost, and quality.
• A genuine passion for building an open, global financial system — with a mindset toward safety, fairness, and responsible AI, especially in financial services.

Nice to Have

• Advanced degree (Master's or PhD) in Computer Science, Machine Learning, Statistics, or a related quantitative field.
• Prior experience building conversational AI systems, chatbots, multi-agent architectures, or customer support automation.
• Experience with large-scale data tools such as Spark, Kafka/Kinesis, Snowflake, or Databricks.
• Familiarity with Apache Airflow or similar DAG-based orchestration tools.
• Experience designing evaluation frameworks, analyzing model performance, and communicating results through clear visualizations and dashboards.
• Experience with responsible AI practices such as model interpretability, bias auditing, or AI governance in regulated industries.

Compensation

The target annual base salary for this position is ₹6,612,600 INR. Total compensation may also include equity and bonus eligibility and benefits (including medical, dental, and vision).