Machine Learning Engineer 2, Business Platform

Intuit seeks a Machine Learning Engineer 2 to join a data science team responsible for conceiving, coding, and deploying data science models at scale. The role emphasizes data preparation, model development and deployment, experimentation through A/B testing and statistical analysis, and the building of agentic systems.

Responsibilities

• Identify data sources, obtain access, import datasets, clean and prepare data, and enable datasets to be “machine learning ready”.
• Collaborate with data scientists to create and refine features from underlying data and to build pipelines used for training and deployment.
• Partner with data scientists to understand, implement, refine, and design machine learning and other algorithms.
• Run recurring A/B tests, collect results, conduct statistical analysis, and draw conclusions regarding model impact.
• Work cross-functionally with product managers, data scientists, and product engineers, communicating findings to peers and leaders.
• Evaluate emerging technology shifts to assess how they may support customer benefits.

Requirements

• BS, MS, or PhD degree in Computer Science or a related field (or equivalent work experience).
• 1+ years of experience.
• Working knowledge of data science tools and frameworks, including Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, and Spark.
• Basic understanding of machine learning techniques such as classification, regression, and clustering.
• Knowledge of machine learning principles including training and validation.
• Familiarity with data query and data processing tools, including SQL.
• Computer science fundamentals including data structures, algorithms, performance complexity, and how computer architecture influences software performance such as I/O and memory tuning.
• Software engineering fundamentals, including version control systems (Git, Github), workflows, and the ability to write production-ready code.
• Experience deploying highly scalable software supporting millions or more users.
• Experience with GPU acceleration, including CUDA and cuDNN.
• Experience integrating applications and platforms with cloud technologies, including AWS and GCP.
• Strong oral and written communication skills, including the ability to lead meetings, present professionally, and explain complex technical concepts to non-technical users.

Technologies

• Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark
• SQL, Git, Github, CUDA, cuDNN
• AWS, GCP

Role Overview

The Machine Learning Engineer 2 will be embedded within a data science organization. The position involves helping conceive, code, and deploy data science models at scale using current industry tools. Key focus areas include data wrangling, scaled model deployments, model development, and building agentic systems.

Location and Compensation

Location: Mountain View, CA (onsite). Salary: USD 140,500 to 190,000 per year.