Software Engineer, Data Scientist
2 months ago
Position Overview
At Autodesk, we're pushing the boundaries of innovation and creativity. As a Software Engineer, you'll be part of a global team that's shaping the future of design, engineering, and manufacturing. We're looking for a talented individual to join our Research team and contribute to the development of cutting-edge machine learning-powered product features.
Key Responsibilities
- Collaborate with researchers and engineers to design and develop scalable data pipelines for machine learning applications.
- Process and prepare large datasets for use with machine learning algorithms.
- Develop and deploy distributed systems to process and filter data in real-time.
- Analyze data to provide insights and inform product development.
- Communicate data findings to stakeholders through data visualizations and reports.
- Ensure data compliance and security best practices are followed.
- Develop and maintain high-quality, well-documented code.
Requirements
- Bachelor's or Master's degree in Computer Science or related field.
- Experience with software version control, unit testing, and deployment pipelines.
- Strong data modeling and architecture skills, with experience working with varied data representations.
- Experience with cloud services and architectures, including AWS and Azure.
- Excellent written communication skills to document code and data findings.
- Experience with relational and NoSQL databases, as well as data processing frameworks like Ray and Metaflow.
Preferred Qualifications
- Experience with computational geometry and mesh data processing.
- Knowledge of statistics and data analysis.
- Ability to communicate complex data findings to non-technical stakeholders.
- Experience with Autodesk products or similar CAD, CAE, and CAM systems.
About Autodesk
Autodesk is a global leader in design, engineering, and manufacturing software. We're committed to empowering creativity and innovation through our products and services. Our Research team is dedicated to pushing the boundaries of what's possible with machine learning and AI.
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