Senior Machine Learning Engineer, Credit Risk

Join Intuit’s Fintech Risk AI/ML credit risk team (Team Apollo) and help protect lending money movement services products by detecting and preventing credit risk. In this onsite role in Mountain View, CA, you’ll work at the intersection of data, machine learning, and production systems, building models and web services that support the team’s risk detection capabilities.

As a Senior Machine Learning Engineer, you’ll be embedded with a data science team and take ownership across the model lifecycle. That includes conceiving, coding, deploying, and scaling machine learning models, supporting feature development, preparing data for training, and running rigorous A/B testing to measure impact.

Responsibilities

• Work embedded with data scientists to conceive, build, and deploy data science models at scale using modern industry tools
• Help develop and maintain web services for the AI team that orchestrate multiple ML functions
• Apply core skills across data wrangling, feature engineering, model development, and evaluation metrics
• Discover data sources, secure access, import data, clean it, and prepare it for machine learning use
• Partner with data scientists to create and refine features from underlying data and build pipelines to train and deploy models
• Collaborate on the implementation, refinement, and design of machine learning and other algorithms
• Run regular A/B tests, gather data, perform statistical analysis, and draw conclusions on model impact
• Coordinate cross-functionally with product managers, data scientists, and product engineers, and communicate results to peers and leaders
• Explore technology shifts and assess how they may connect with customer benefits

Requirements

• BS, MS, or PhD in Computer Science or a related field, or equivalent work experience
• 6+ years of experience
• Knowledge of data science tools and frameworks, including Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, and Spark
• Understanding of machine learning principles such as training and validation
• Demonstrated experience with web services (for example, REST) and API design
• Experience with object-oriented languages such as Scala, Python, or Java (preferred)
• Knowledge of data query and data processing tools, including SQL
• Computer science fundamentals: data structures, algorithms, performance complexity, and how computer architecture affects software performance (I/O and memory tuning)
• Software engineering fundamentals: version control (for example, Git) and workflows, with the ability to write production-ready code
• Experience deploying highly scalable software supporting millions or more users
• Experience with GPU acceleration (for example, CUDA and cuDNN)
• Experience integrating applications and platforms with cloud technologies (for example, AWS)
• Strong oral and written communication skills, including conducting meetings and making professional presentations to non-technical users

Technology Stack

Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark, REST, Scala, Java, SQL, Git, CUDA, cuDNN, AWS

Compensation: USD 171,000 - 231,500 per year.