Senior ML Platform Engineer - Remote-First, Scalable ML Infra

Coinbase; United States; Hybrid; USD 191,000 - 225,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k)

Equity

Bonus eligibility

Job summary

Coinbase is seeking a Senior Machine Learning Platform Engineer to build foundational ML infrastructure powering feature engineering, model training, and serving. You will own systems across streaming, training, and inference, shaping how ML scales company-wide.

Responsibilities include designing reliable inference services, low-latency pipelines, training orchestration, and observability. Mentoring others and upholding responsible AI practices are essential components of the role.

Qualifications

• 5+ years of industry experience as a software engineer, with distributed systems in production.
• Built and operated low-latency data or ML infrastructure processing data at scale.
• Mentored engineers and raised team engineering quality through reviews.
• Familiar with ML platform components sufficient to partner with ML engineers.
• Uses generative AI responsibly with human oversight to improve workflow efficiency.

Responsibilities

• Own the design and reliability of ML inference infrastructure serving models.
• Build and optimize low-latency streaming pipelines for production features.
• Drive improvements to distributed training infrastructure for scalable workloads.
• Develop observability tooling to monitor data quality entering models.
• Mentor junior engineers and raise engineering standards over time.

Skills

Distributed systems

Low-latency infra

Mentoring

ML platform

Generative AI governance

Tools

Model serving frameworks

Job description

Coinbase is seeking a Senior Machine Learning Platform Engineer to build foundational ML infrastructure powering feature engineering, model training, and serving. You will own systems across streaming, training, and inference, shaping how ML scales company-wide.

Responsibilities include designing reliable inference services, low-latency pipelines, training orchestration, and observability. Mentoring others and upholding responsible AI practices are essential components of the role.