Parallel is hiring a
- USA Only
- 0 applicants (0%)
Time zones: EST (UTC -5) CST (UTC -6) MST (UTC -7) PST (UTC -8) AKST (UTC -9) HST (UTC -10)
This job is for FedML (https://www.fedml.ai/) posted via Parallel. This is a full-time role.
- Participate in the development of machine learning platform and open source communities
- Responsible for the foundational research and product development, and continuously improve the R&D efficiency
- Responsible for feature development, algorithm optimization of the platform, improving user experience and usability through cutting-edge or mature technologies
- Participate in or lead design reviews with peers and stakeholders to decide amongst available technologies;
- Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Bachelor’s degree or equivalent practical experience in computer science or related areas.
- 2 years of experience with data structures or algorithms in either an academic or industry setting.
- Good communication and writing skills in English environment.
- Information Systems Or Computer Science Master’s Degree OR equivalent industry experience
- 2+ years of professional experience in Product Management
- Prior experience building AI/machine learning products for both on premise and Public Cloud
- Top notch written and oral communication skills, including experience presenting to executive leadership, participating in the sales cycle, and handling sensitive customer escalations
- Demonstrated experience in gathering and transforming product requirements into an actionable product roadmap
- Experience working and delivering product or services in an agile/lean environment
- Track record of successfully building alliances with teams in a matrix environment
- Experience building and delivering solution on AWS, Azure, GCP in a dynamic and automated environment
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