Senior ML Platform Engineer - Remote, Low-Latency Inference

Coinbase, Inc.

Saint Paul (MN)

Hybrid

USD 191,000 - 225,000

Full time

7 days ago
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Job summary

Coinbase, Inc. is seeking a Senior Machine Learning Platform Engineer to design and operate the ML inference infrastructure powering fraud detection, personalization, and blockchain analysis.

You will own streaming pipelines and distributed training, enabling scalable feature data and model serving across the company. The role emphasizes reliability, observability, and mentorship, with remote-first work and quarterly in-person surges.

Qualifications

  • 5+ years of industry experience building production software with distributed systems.
  • Experience designing and operating low-latency ML infrastructure.
  • Proven track record mentoring engineers and raising engineering standards.
  • Familiarity with ML platform components (feature stores, model serving, training orchestration).
  • Experience using generative AI responsibly with human oversight.

Responsibilities

  • Own design and reliability of ML inference infrastructure at scale.
  • Build and optimize low-latency streaming pipelines delivering fresh feature data.
  • Improve distributed training infrastructure for large data volumes.
  • Develop observability tooling to monitor data quality and model performance.
  • Mentor junior engineers to raise production-grade software quality.

Skills

Distributed systems
Streaming pipelines
Mentoring engineers
ML platform components
Generative AI governance

Tools

Feature stores
Model serving frameworks
Training orchestration

Job description

Coinbase, Inc. is seeking a Senior Machine Learning Platform Engineer to design and operate the ML inference infrastructure powering fraud detection, personalization, and blockchain analysis.

You will own streaming pipelines and distributed training, enabling scalable feature data and model serving across the company. The role emphasizes reliability, observability, and mentorship, with remote-first work and quarterly in-person surges.

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