Senior Software Engineer, Machine Learning

Deliver scalable production machine learning services to solve liquidity challenges. Build the next generation of payment applications that enable banks to settle cross-border payments through applying data engineering, machine learning, and software engineering. Design and implement tools and processes for the entire machine learning lifecycle, including feature generation, model development, model deployment, model serving, and experimentation. Build platforms and tools to enable scalable, auditable, and maintainable machine learning services at Ripple. Prototype solutions for complex software problems and implement them for on premise, cloud deployments, and use cases. Analyze user needs to engineer software solutions, modify existing software, and improve software performance. Monitor computer applications functioning to ensure specifications are met. Apply technical skills to effectively troubleshoot and thoroughly resolve the root cause of defects. Continuously raise Ripple’s standard of engineering excellence by implementing and driving best practices for coding, testing, and deployment. Communicate and collaborate with other Ripple engineers and applied scientists to bring the benefits of machine learning solutions to our customers and improve Ripple’s products. Telecommuting permitted 100% - may live anywhere in the U.S.

MINIMUM REQUIREMENTS: 

Must have a Master’s degree in Computer Science or a related field plus 1 year of experience in machine learning engineering.

Of the required experience, must have 1 year of experience in each of the following (which may be gained concurrently): 

• Complete software development lifecycle;
• Developing on one or more cloud services (such as GCP or AWS);
• Translating business requirements into technical requirements to build out modularized software architecture;
• Authoring and reviewing software design and code;
• Building and improving production quality machine learning models for classification, regression, forecasting or natural language processing problems; 
• Post deployment management, debugging and monitoring of machine learning models and data pipelines; and
• Software deployment or MLOps concepts in relation to model lifecycle management

Telecommuting permitted 100% - may live anywhere in the U.S.

For positions that will be based in CA, the annual salary range for this position is $174,410 - $175,000. Actual salaries may vary based on numerous factors including, among other things, an individual applicant’s experience and qualifications for the position.

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