Lead the design, development, and deployment of production-grade ML systems across the organization.
Work with Ibotta architecture and Machine Learning Platform teams to ensure integration of machine learning services and pipelines in larger technology infrastructure.
Act as a liaison between technical teams and non-technical stakeholders to communicate complex concepts clearly.
Communicate complex machine learning solutions, concepts and the results of analyses in a clear and effective manner to business stakeholders and technology leaders to maximize the effectiveness of machine learning initiatives.
Mentor ML Engineers and Data Scientists, fostering a culture of technical ownership, rigorous experimentation, and best practices.

Requirements

6+ years of professional industry experience as a Machine Learning Engineer or Software Engineer, focused on deploying machine learning systems at scale.
Advanced knowledge of multiple ML frameworks like: Sklearn, TensorFlow, Sagemaker, Spark ML.
Expertise working with distributed big-data tools and event-based architectures, ideally Spark and Kafka.
Deep hands-on experience prototyping, building, releasing, and monitoring mission-critical machine learning models in high traffic applications.
Experience working within a cloud-based infrastructure, ideally AWS.
Track record of mentoring junior engineers or leading cross-functional initiatives.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningML frameworksSklearnTensorFlowSagemakerSpark MLbig-data toolsevent-based architecturesAWSmonitoring machine learning models

Soft Skills

communicationmentoringtechnical ownershiprigorous experimentationcross-functional leadership