Senior Machine Learning Platform Engineer

Coinbase

. Build foundational infrastructure for feature engineering, model training, and model serving across Coinbase .

Posted 9/17/2026full-timeRemote • United StatesSenior💰 $191,250 - $225,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and optimizing low-latency ML infrastructure and streaming pipelines, with a strong focus on reliability and observability. Proven ability to mentor engineers and enhance engineering standards through technical leadership and code reviews.

Highest-signal resume keywords

Distributed Systems OwnershipLow-Latency Data InfrastructureStreaming Pipeline DevelopmentML Platform Components FamiliarityTechnical Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Model TrainingModel ServingFeature EngineeringData Quality MonitoringDistributed Training InfrastructurePredictive ModelsGenerative AIObservability ToolingHigh Availability SystemsLow Latency Optimization

Soft Skills

MentoringTechnical LeadershipCode Review

Industry Keywords

Machine LearningFraud DetectionUser PersonalizationBlockchain Analysis

Tech Stack

Tools & technologies

Distributed Systems

About the role

Key responsibilities & impact

Build foundational infrastructure for feature engineering, model training, and model serving across Coinbase
Own the design and reliability of ML inference infrastructure for predictive models and LLMs
Maintain high availability and low latency at scale
Build and optimize low-latency streaming pipelines delivering fresh, high-quality feature data to production ML models
Improve distributed training infrastructure for efficient processing of large data volumes
Develop observability tooling to monitor data quality and detect degradations affecting model performance
Mentor junior engineers and raise team engineering standards
Support fraud detection, user personalization, and blockchain analysis

Requirements

What you’ll need

5+ years of industry experience as a software engineer
Demonstrated ownership of distributed systems in production environments
Experience building and operating low-latency data or ML infrastructure, including streaming pipelines, online serving systems, or distributed training, at scale
Track record of mentoring engineers and raising engineering quality through code reviews, design reviews, and technical leadership
Familiarity with ML platform components, including feature stores, model serving frameworks, and training orchestration
Responsible use of generative AI with human oversight to deliver business-ready outputs and measurable workflow improvements in efficiency, cost, and quality

Benefits

Comp & perks

Equity eligibility
Bonus eligibility
Medical insurance
Dental insurance
Vision insurance
401(k)
Quarterly in-person working sessions (“surges”)
Reasonable accommodations for individuals with disabilities
Equal opportunity employment protections