Staff AI/ML Engineer, Data Exchange
Description For Staff AI/ML Engineer, Data Exchange
Join Intuit's Data Exchange group as a Staff Machine Learning Engineer, where you'll be part of a team responsible for processing millions of transactions and statements daily across all Intuit products. This role combines technical leadership with hands-on development, focusing on developing and maintaining machine learning models using both analytical algorithms and deep learning approaches. You'll be working with Intuit's Data Acquisition Platform, leading ML project lifecycle management, and collaborating across multiple teams. The position offers the opportunity to work with cutting-edge AI technologies while directly impacting Intuit's global financial technology platform that serves approximately 100 million customers worldwide through products like TurboTax, Credit Karma, QuickBooks, and Mailchimp. You'll be responsible for architecting, integrating, and optimizing ML models at scale, while working in a collaborative environment with product managers, data scientists, and engineers. This hybrid role requires strong technical expertise in ML, software engineering, and communication skills, making it ideal for someone who wants to lead technical innovation while delivering practical business solutions.
Responsibilities For Staff AI/ML Engineer, Data Exchange
- Design and build systems which improve machine learning scalability, usability, and performance
- Own end-to-end model development lifecycle, including defining problems, featurization, model exploration, deployment, and performance monitoring
- Collaborate with stakeholders to define success criteria and align model metrics with business goals
- Work with product managers, business analytics, data scientists, and backend engineers
- Explore state-of-the-art technologies and apply them to deliver customer benefits
- 50% hands-on coding
Requirements For Staff AI/ML Engineer, Data Exchange
- 6+ years industry experience bringing AI models from modeling to production
- Experience in modern, advanced analytical tools and programming
- Expertise in data mining algorithms and statistical modeling techniques
- Strong understanding of Software design and architecture process
- Experience working in cloud production-grade high-scale microservices environment
- Proficiency in Python, Java, or Scala
- Expertise with Spark for data manipulation and featurization
- Efficient in SQL, Hive, or SparkSQL
- Comfortable in Linux environment
- Familiar with backend services: K8S, Spring Boot, Vert.x, Docker
- Excellent oral and written English communication skills
- BS, MS, or PhD in Computer Science, Statistics, Applied Math, Operations Research, or equivalent work experience
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