Machine Learning Engineer 2, Business Platform
Python
A/B Testing
Advanced Analytics
Ai Ml
Analytics
Artificial Intelligence
AWS
Big Data
Bigdata
Cloud Platforms
Data Analysis
Data Analytics
Data Integration
Data Pipeline
Data Platform
Data Processing
Data Science
Database
Databases
Deep Learning
Digital Marketing
Engineer
Google Cloud Platform
Machine Learning
Machine Learning Engineer
Machine Learning Pipelines
Marketing Analytics
Programming
Programming Language
Programming Languages
SQL
Statistical Modeling
TensorFlow
User Research
Job Description
Intuit is hiring a Machine Learning Engineer 2 embedded in a data science team to conceive, code, and deploy data science models at scale.
Responsibilities
- Discover data sources, obtain access, import data, clean and prepare it to be machine learning ready
- Partner with data scientists to create and refine features and build pipelines for training and deployment
- Collaborate on machine learning and other algorithms: implement, refine, and support design efforts
- Run recurring A/B tests, collect results, perform statistical analysis, and draw conclusions on model impact
- Work cross-functionally with product managers, data scientists, and product engineers; communicate findings to peers and leaders
- Explore new technology shifts and assess how they can connect to customer benefits
Requirements
- BS, MS, or PhD in Computer Science or a related field, or equivalent work experience
- 1+ years of experience
- Knowledge of data science tools and frameworks: Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark
- Basic understanding of machine learning techniques: classification, regression, clustering
- Understanding of machine learning principles such as training and validation
- Knowledge of data query and processing tools: SQL
- Computer science fundamentals: data structures, algorithms, performance complexity, and how computer architecture impacts software performance (including I/O and memory tuning)
- Software engineering fundamentals: version control systems (such as Git and GitHub), workflows, and ability to write production-ready code
- Experience deploying highly scalable software supporting millions or more users
- Experience with GPU acceleration (such as CUDA and cuDNN)
- Experience integrating applications and platforms with cloud technologies (such as AWS and GCP)
- Strong oral and written communication, including leading meetings and presenting complex technical material to non-technical users
Tech Stack
- Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark
- SQL, Git, GitHub
- CUDA, cuDNN
- AWS, GCP
Role Overview
- Embedded in a data science team to help conceive, code, and deploy data science models at scale
- Focus areas include data wrangling, scaled model deployments, model development, and building agentic systems
Location: Mountain View, CA (onsite)
Compensation: USD 140,500 - 190,000 per year
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