Senior ML Platform Engineer: Scale Inference & Streaming

Coinbase, Inc.; Montpelier (VT); Hybrid; USD 191,000 - 225,000; Full time

Benefits offered by this job

Remote-friendly

Quarterly in-person surges

Job summary

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

You will mentor engineers, collaborate with ML teams, and ensure data quality and governance for production ML workloads.

Qualifications

• 5+ years of industry experience as a software engineer with distributed systems in production.
• Built and operated low-latency ML infrastructure (streaming pipelines, online serving systems, or distributed training).
• Mentored engineers and raised engineering quality through code/design reviews.
• Familiarity with ML platform components (feature stores, model serving frameworks, training orchestration).
• Careful use of generative AI with human oversight to improve workflows, cost and quality.

Responsibilities

• Own the design and reliability of ML inference infrastructure at scale.
• Build and optimize low-latency streaming pipelines delivering fresh feature data.
• Drive improvements to distributed training infrastructure for efficiency.
• Develop observability tooling to monitor data quality and model performance.
• Mentor junior engineers to raise the team's engineering standards.

Skills

Distributed systems

Streaming pipelines

Model serving

Mentoring engineers

Low-latency infra

ML platforms

Leadership

Tools

Feature stores

Model serving frameworks

Training orchestration

Observability tooling

Job description

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

You will mentor engineers, collaborate with ML teams, and ensure data quality and governance for production ML workloads.