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Ibotta · 4 hours ago

Machine Learning Engineer

Denver, CO

Full-time

Hybrid

Entry, Mid Level

$136K/yr - $158K/yr

2+ years exp

Ibotta is a leading performance marketing platform seeking a Machine Learning Engineer to join their Core Data & Analytics team. The role involves building scalable machine learning solutions and collaborating with various teams to enhance the organization's ML strategy and practices.

AppsCouponsE-CommerceMobileMobile AppsRetailService IndustryShopping

No H1B

Responsibilities

Design, develop and deploy large scale, big data-driven machine learning models that are integrated with key product features

Build and scale ML related infrastructure to help streamline the development, evaluation, deployment, and re-usability of core ML features and services

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

Analyze, and at times build, large and novel datasets to extract actionable insights to inform model development and understand customer behavior and or product performance

Collaborate with Machine Learning Engineers and Data Scientists to establish standards and solutions that scale and can be leveraged in various initiatives throughout the organization

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

Qualification

Machine LearningPythonSQLSparkMachine Learning FrameworksCI/CDCommunication SkillsCritical ThinkingContinuous Learning

Required

2+ years of professional experience as a Machine Learning Engineer, Data Scientist, or equivalent role, focusing on machine learning, statistical modeling, and/or ML infrastructure

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

Strong SQL knowledge and experience with manipulating complex data to apply business rules for improved feature engineering within data lakes, distributed systems, and data streams

Proficiency in Python

Experience working with machine learning frameworks (e.g. scikit-learn, xgboost) and distributed big-data tools (Spark, Hive)

Experience building and maintaining realtime model endpoints/APIs

Ability to communicate complex, technical machine learning implementations to diverse audiences

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

A love of learning and continuous development, including staying at the forefront of the latest advances in data science and machine learning

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