Principal Machine Learning Engineer

Ibotta is a performance marketing platform that helps brands deliver digital promotions to consumers through its publisher network. The company is seeking a Principal Machine Learning Engineer to lead the strategy, design, deployment, and scaling of machine learning architectures, platforms, and production systems. The role will provide technical leadership, collaborate across teams, communicate with stakeholders, and mentor Machine Learning Engineers and Data Scientists.

Responsibilities:

• Research, design, and deploy the next generation of Ibotta's ML architectures, workflows, and standards that seamlessly integrate with key product features 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
• Be the leading contributor, voice, and thought leader in a growing community of machine learning practitioners
• Identify, research, prototype and evaluate cutting edge big data and machine learning technologies
• Act as a liaison between technical teams and non-technical stakeholders to communicate complex concepts clearly
• Lead the design, development, and deployment of production-grade ML systems across the organization
• 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:

• 10+ 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
• Extensive experience working within a cloud-based infrastructure, ideally AWS
• Experience driving org-wide ML strategy or setting technical standards across teams
• Track record of mentoring senior engineers or leading cross-functional initiatives
• Comfort operating with ambiguity and influencing without direct authority
• Applicants must be currently authorized to work in the United States on a full-time basis