- Create tools for migrating large bodies of user data across systems for new products, scalability efforts, and development of new core infrastructure.
- Use machine learning, statistics, or other data techniques to build algorithms.
- Develop highly scalable classifiers and tools leveraging machine learning, regression, and rules based models.
- Utilize technical research background, train new ranking models, and run experiments.
- Suggest, collect, and synthesize system requirements from stakeholders and create effective feature roadmaps.
- Code deliverables in tandem with the engineering team.
- Adapt standard machine learning methods to best exploit modern parallel environments (e.g.
- distributed clusters, multicore SMP, and GPU).
- Telecommuting is permitted from anywhere in the United States.
- Requires a Master's degree in Computer Science, Engineering, Computational Science and Engineering, Mathematics, or a related field.
- Completion of one graduate-level course, project, or internship (including experience as a Research Assistant) involving each the following:
- 1. Advanced machine learning research and development
- 2. Programming and software development
- 3. Data analysis and modeling
- 4. Algorithm design and optimization, data structure
- 5. Problem-solving and critical thinking, solving analytical problems with quantitative approaches
- 6. Machine learning system design and deployment
- 7. Gathering and process data from varying sources
- 8. Python, C++, PHP, MySQL and
- 9. Cloud computing and big data technologies.
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