Title: Product Innovation
Location: Beaverton, OR
Duration: 6 month contract
What you will do
In product/systems improvement projects: uses machine language and statistical modeling techniques such as decision trees, logistic regression, Bayesian analysis and others to develop and evaluate algorithms to improve product/system performance, quality, data management and accuracy. In both theoretical development environments and specific product design, implementation and improvement environments, uses current programming language and technologies to translate algorithms and technical specifications into code.
Skills
- Develop and program integrated software algorithms to structure, analyze and leverage data in product and systems applications in both structured and unstructured environments.
- Develop and communicate descriptive, diagnostic, predictive and prescriptive insights/algorithms.
- Completes programming and implements efficiencies, performs testing and debugging.
- Completes documentation and procedures for installation and maintenance.
- Applies deep learning technologies to give computers the capability to visualize, learn and respond to complex situations.
- Adapts machine learning to areas such as virtual reality, augmented reality, artificial intelligence, robotics and other products that allow users to have an interactive experience.
- Can work with large scale computing frameworks, data analysis systems and modeling environments.
- Experience with Machine Learning Operations and Infrastructure.
- Experience with multidimensional time series and motion data (3d/mocap ideal), computer vision/image processing, signal processing (accelerometer, signal processing experience)
- Experience with supervised and unsupervised ML (ensemble methods, clustering)
Technical
- Python + Pandas
- ML libs: Scikit-learn, xgboost, etc.
- Data processing libs like scikit-image/Pillow, scipy
- Jupyter (local) and (AWS Boto + Sagemaker or Databricks)
- Some SQL and NoSQl + python libs for managing interaction (ex. sqlalchemy)
- Sagemaker Pipelines and Endpoints
- Familiarity with software engineering basics (ex. git feature branch workflow, python dependency management, etc.)