Overview
Join Intuit as a Senior Machine Learning Engineer and be part of a dynamic team of data scientists. In this role, you will be responsible for conceiving, coding, and deploying data science models at scale using the latest industry tools. Your expertise in data wrangling, feature engineering, model development, and testing metrics will be crucial to our success.
What You'll Bring
- Education: BS, MS, or PhD in Computer Science or a related field, or equivalent practical experience.
- Experience: 6+ years in the field.
- Technical Skills:
- Proficiency with Data Science tools and frameworks such as Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, and Spark.
- Basic knowledge of machine learning techniques including classification, regression, and clustering.
- Understanding of machine learning principles such as training and validation.
- Knowledge of data query and processing tools like SQL.
- Strong foundation in computer science fundamentals: data structures, algorithms, performance complexity, and the implications of computer architecture on software performance (e.g., I/O and memory tuning).
- Software engineering fundamentals: version control systems (e.g., Git, Github) and workflows, with the ability to write production-ready code.
- Experience deploying highly scalable software supporting millions of users.
- Experience with GPU acceleration (e.g., CUDA and cuDNN).
- Experience integrating applications and platforms with cloud technologies (e.g., AWS and GCP).
- Communication Skills: Strong oral and written communication skills, with the ability to conduct meetings, make professional presentations, and explain complex concepts to non-technical users.
How You Will Lead
- Discover and access data sources, import them, clean them up, and prepare them for machine learning.
- Collaborate with data scientists to create and refine features from underlying data and build pipelines to train and deploy models.
- Partner with data scientists to understand, implement, refine, and design machine learning and other algorithms.
- Conduct regular A/B tests, gather data, perform statistical analysis, and draw conclusions on the impact of your models.
- Work cross-functionally with product managers, data scientists, and product engineers, and communicate results to peers and leaders.
- Explore new technology shifts to determine how they might connect with the customer benefits we wish to deliver.
This is a hybrid role based in San Diego, CA, where you will have the flexibility to work both on-site and off-site.
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