Senior ML Platform Engineer - Remote-First, Scale Inference

Coinbase, Inc.; Atlanta (GA); Remote; USD 191,000 - 225,000; Full time

Job summary

Coinbase is seeking a Senior Machine Learning Platform Engineer to build and scale the infrastructure powering feature engineering, model training, and model serving. You will own systems across streaming, distributed training, and high-availability inference services, directly shaping ML scale across the company.

Responsibilities include designing reliable ML inference, building low-latency pipelines, and mentoring engineers to improve production-grade software.

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 (streaming pipelines, online serving systems, or distributed training).
• Proven mentoring experience and ability to raise team engineering quality.
• Familiarity with ML platform components to partner effectively with ML engineers.
• Uses generative AI responsibly with human oversight to improve workflow efficiency, cost, and quality.

Responsibilities

• Own the design and reliability of ML inference infrastructure 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 process large data volumes efficiently.
• Develop observability tooling to monitor data quality and detect model degradations.
• Mentor junior engineers to raise engineering standards over time.

Skills

Distributed systems

Low-latency infra

Mentoring

ML platform components

Generative AI governance

Tools

Streaming pipelines

Model serving frameworks

Distributed training

Job description

Coinbase is seeking a Senior Machine Learning Platform Engineer to build and scale the infrastructure powering feature engineering, model training, and model serving. You will own systems across streaming, distributed training, and high-availability inference services, directly shaping ML scale across the company.

Responsibilities include designing reliable ML inference, building low-latency pipelines, and mentoring engineers to improve production-grade software.