Machine Learning Engineer, Platform

Ibotta is seeking a Machine Learning Engineer (Platform) to help build ML systems that drive our company’s mission to Make Every Purchase Rewarding for millions of consumers. We're looking for someone who has a passion for building scalable machine learning and MLOps platforms using technologies such as Python, Databricks, Spark, AWS, Airflow, Terraform, etc. Every member of the team has input into our roadmap and will have a real impact as part of a small, agile team.

This position is located in Denver, Colorado as a hybrid position requiring 3 days in office (Tuesday, Wednesday, and Thursday). Candidates must live in the United States.

What you will be doing:

• Design and develop systems that support the creation of large scale, big-data driven, machine learning models integrated into our product. Some examples of potential projects include:

  • Building/scaling MLOps infrastructure to help streamline the development, evaluation, deployment, and re-usability of core ML features and services.

  • Building, creating, and iterating on core reusability components for feature engineering, model development, model deployment, and more.

  • Enabling other members of the data science and analytics community with tools, processes, and standards.

• Collaborate with Machine Learning Engineers and Analytics leaders to establish standards and platforms that scale and can be leveraged in various initiatives throughout the organization

• Deliver world class products in partnership with cross functional teams (ML Engineers, Data Engineers, Software Engineers, Data Scientists, etc.)

• 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

• Embrace and uphold Ibotta’s Core Values: Integrity, Boldness, Ownership, Teamwork, Transparency and A good idea can come from anywhere

What we are looking for:

• 2+ years of professional experience as a MLOps Engineer, Data Engineer, or equivalent role, focusing on machine learning and/or ML infrastructure

• Bachelor’s Degree in Computer Science, Mathematics, Analytics, or related field required

• Ability to think critically and leverage domain expertise to build machine learning powered libraries/infrastructure that help to achieve high-level business objectives

• Proficiency in Python and SQL

• Experience working with machine learning frameworks (e.g. scikit-learn, XGBoost, PyTorch, TensorFlow) and distributed big-data tools (e.g. Spark) is a plus

• Experience working with version control systems (e.g. git) and CI/CD for machine learning pipelines

• Experience with Databricks, Airflow, Docker, and Terraform is a plus