Senior Staff Machine Learning Engineer, Coinbase

• 12+ yrs of industry experience as a machine learning engineer
• Experience with at least one ML model: Logistic Regression, Gradient Boosting trees, Deep learning, etc
• Experience with data analysis, feature exploration, ETL, and visualization
• Experience in one or more of the following: data mining, information retrieval, advanced statistics or natural language processing, computer vision
• Experience building backend systems at scale with a focus on data processing/machine learning/analytics
• Exhibit our core cultural values: add positive energy, communicate clearly, be curious, and be a builder

Desirable

• As a Senior Staff Machine Learning engineer at Coinbase, you will be a steward of our architecture, operations, scale, and security. you’ll be building the critical infrastructure for the open financial system -- tapping into a variety of large data sources such as the blockchain -- to provide millions of people access to crypto while detecting and preventing bad actors
• You’ll not only have the chance to drive significant impact from protecting Coinbase, you’ll also leverage machine learning to make our product delightful by adding intelligence to news, notifications, risk, and much more
• You will help us recruit and develop world-class engineers that represent the best in the industry
• You will look outward as well as inward, aligning our executive team and product strategy with changes in technology, and help us create an innovative culture
• While you need to be strategic in your thinking, this is also very much a “hands-on” job - there are no ivory towers or “architect-only” roles
• You should be able to dive deep into code and implement complex systems where necessary
• You must be willing to operate without boundaries and be able and willing to fix problems anywhere you find them
• Build and launch excellent productionalized, low-maintenance models
• Build features and success metrics by disambiguating requirements
• Leverage state of the art machine learning techniques for a variety of problems across the company including fraud, feed ranking, recommendations and targeting, blockchain mining
• Setup A/B experiments and iterate until impact is landed