Senior ML Platform Engineer — Low-Latency, Scalable Infra

Coinbase, Inc.; Washington (District of Columbia); Hybrid; USD 191,000 - 225,000; Full time

Benefits offered by this job

Equity eligibility

Bonus eligibility

Medical, dental, vision

401(k)

Job summary

Coinbase, Inc. is seeking a Senior Machine Learning Platform Engineer to build foundational ML infrastructure across feature engineering, training, and serving. You will influence systems handling fraud detection, personalization, and blockchain analysis, spanning streaming, training, and inference at scale.

You will own high-availability inference services, collaborate with ML engineers, and mentor others to raise engineering standards while delivering business-ready outputs.

Qualifications

• 5+ years of industry experience as a software engineer with ownership of distributed systems in production.
• Built and operated low-latency data or ML infrastructure (streams, online serving, or distributed training) processing data at scale.
• Proven mentoring experience and improving engineering quality via reviews and design discussions.
• Familiarity with ML platform components to partner with ML engineers as a platform builder.
• Responsible use of generative AI with human oversight to improve workflow efficiency, cost, and quality.

Responsibilities

• Own the design and reliability of ML inference infrastructure powering predictive models and LLMs with high availability and low latency.
• Build and optimize low-latency streaming pipelines delivering fresh feature data to production models.
• Improve distributed training infrastructure to enable efficient processing of large data volumes.
• Develop observability tooling to monitor data quality entering models and detect degradations.
• Mentor junior engineers to raise engineering standards and production-readiness.

Skills

Distributed systems

ML infrastructure

Mentoring

ML platform components

Generative AI usage

Job description

Coinbase, Inc. is seeking a Senior Machine Learning Platform Engineer to build foundational ML infrastructure across feature engineering, training, and serving. You will influence systems handling fraud detection, personalization, and blockchain analysis, spanning streaming, training, and inference at scale.

You will own high-availability inference services, collaborate with ML engineers, and mentor others to raise engineering standards while delivering business-ready outputs.