Senior ML Platform Engineer - Real-Time Inference

Coinbase, Inc.; Trenton (NJ); Remote; USD 191,000 - 225,000; Full time

Job summary

Coinbase, Inc. seeks an experienced Senior Machine Learning Platform Engineer to build and scale ML infrastructure powering feature engineering, model training and serving. You will influence fraud detection, personalization and blockchain analytics while shaping streaming, training and inference services.

You will own reliable ML inference, streaming pipelines and distributed training, mentoring others and ensuring high-quality, production-grade software with responsible AI practices.

Qualifications

• 5+ years as a software engineer with distributed systems in production.
• Built low-latency data or ML infrastructure.
• Mentored engineers and raised engineering quality through reviews.
• Familiarity with ML platform components to partner with ML engineers.
• Uses generative AI responsibly with human oversight.

Responsibilities

• Own the design and reliability of ML inference infrastructure serving both predictive models and LLMs, maintaining high availability and low latency at scale.
• Build and optimize low-latency streaming pipelines that deliver fresh, high-quality feature data to production ML models.
• Drive improvements to distributed training infrastructure, enabling ML engineers to process large data volumes efficiently.
• Develop observability tooling to monitor data quality entering models and detect degradations impacting model performance.
• Mentor junior engineers on building production-grade software, raising the team's engineering standards over time.

Job description

Coinbase, Inc. seeks an experienced Senior Machine Learning Platform Engineer to build and scale ML infrastructure powering feature engineering, model training and serving. You will influence fraud detection, personalization and blockchain analytics while shaping streaming, training and inference services.

You will own reliable ML inference, streaming pipelines and distributed training, mentoring others and ensuring high-quality, production-grade software with responsible AI practices.