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# CONTRACT - Engineer, Data Scientist (NTD)

- **Company:** Nintendo of America Inc.
- **Location:** Redmond, WA, United States
- **Experience:** Experienced
- **Salary:** $117,395.0 - $211,307.0
- **Contract:** Permanent contract
- **Skills:** Artificial Neural Networks, C Sharp (Programming Language), C++ (Programming Language), Python (Programming Language), Tensorflow, Pytorch, Deep Learning, Git
- **Published:** July 24, 2026
- **Apply:** https://jobs.localjobnetwork.com/apply/add/86085531/1

## About the Role

* 3+ years of professional experience as a data scientist
 * 3+ years of professional experience working with deep learning libraries (PyTorch and/or TensorFlow)
 * Proficient in Python
 * Possess strong debugging and troubleshooting skills
 * Familiar with Git workflow
 * Experience with C, C++, or C# is a plus
 * BS in CS/Applied Mathematics/Statistics/DS/ML or related field

Applicants must be legally eligible to work in the United States to be considered. Visa sponsorship is not available for this role.
This position is onsite in Redmond, WA, and not open to remote status at this time.

This contract position includes the base pay range listed below and is eligible for benefits through the employing agency. Agency benefits include eligibility for medical insurance, employee assistance program, and paid sick leave. All benefits are subject to elections, eligibility requirements, plan and program terms. Benefits offerings will be confirmed at the time of offer by the employing agency, and may differ depending on the employing agency partner.

## Description

Nintendo is an equal opportunity employer. We offer a welcoming and inclusive environment in service to one another, our products, the diverse consumers we represent, and the communities we call home. We do all of this with kindness, empathy and respect for each other.
DESCRIPTION OF DUTIES

 * Train, evaluate, and optimize neural networks
 * Write scripts to facilitate neural network model development and use
 * Procure and clean data necessary for training and evaluating models
 * Effectively communicate with other teams, especially as it relates to domain-specific knowledge, model quality, and model performance
 * Document work according to defined processes


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