Machine Learning Engineer

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Embedded inside a vibrant team of data scientists, you’ll conceive, code, and deploy data science models at scale using industry tools. Key skills: data wrangling, feature engineering, model development, and metric testing.

• Discover data sources, grant access, import, clean, and prepare them for machine learning.
• Partner with data scientists to create and refine features, build training pipelines, and deploy models.
• Run A/B tests, gather data, perform statistical analysis, and draw conclusions on model impact.
• Collaborate cross‑functionally with product managers, data scientists, and product engineers to communicate results to peers and leaders.
• Explore technology shifts and determine how they connect with customer benefits.

• BS, MS, or PhD in Computer Science or related field, or equivalent practical experience.
• Knowledgeable with data science tools and frameworks (Python, scikit-learn, NLTK, Num Py, pandas, Tensor Flow, Keras, R, Spark).
• Basic knowledge of machine learning techniques (classification, regression, clustering).
• Experience building prototype ML models, productionalizing prototypes, and enhancing model performance.
• Strong problem‑solving and communication skills.

Intuit offers a competitive compensation package with a strong pay‑for‑performance approach. Eligible for cash bonus, equity rewards, and benefits. Pay ranges:
Bay Area, CA: $137,500 – $186,500
Southern California, CA: $124,500 – $168,500
New York, NY: $136,000 – $184,000

Sunnyvale, CA; active hiring;