Machine Learning Engineer/AI Engineer- (3838-1) Experience in Jupyter eco-system
San Francisco, CA - 94111 (After Covid)
6 Months + with Further Extension
Immediate Need and Direct Client !
Must have experience implementing modifications to the Jupyter eco-system including Jupyterlab and Jupyterhub
- Responsible for developing, implementing and maintaining knowledge-based or artificial intelligence application systems. The individual should ensure that information is converted into a format that is digestible and easy for end users to access the information and utilize it optimally.
Designs and writes complex code in several languages relevant to our existing product stack, with a focus on automation
- Configures, tunes, maintains and installs applications systems and validates system functionality
- Monitors and fine tunes applications system to achieve optimum performance levels and works with hardware teams to resolve issues with hardware and software
- Develops and maintains department's knowledge database containing enterprise issues and possible resolutions.
- Develops models of task problem domain for which a system will be designed or built.
- Uses models, hypotheses, and cognitive analysis techniques to elicit real problem-solving knowledge from the experts
- Mediates between the expert and knowledge base; encodes for the knowledge base
- Acts as subject matter expert for difficult or complex application problems requiring interpretation of AI tools and principles
- Researches and prepares reports and studies on various aspects of knowledge acquisition, modeling, management, and presentation
- Develops and maintains processes, procedures, models, and templates for collecting and organizing knowledge into specialized knowledge representation programs
- Acts as vendor liaison for products and services to support development tools
- Maintains the definition, documentation, training, testing, and activation of Disaster Recovery/Business Continuity Planning to meet compliance standards
- Maintains a comprehensive operating system hardware and software configuration database/library of all supporting documentation to ensure data integrity
- Acts to improve the overall reliability of systems and to increase efficiency
- Works collaboratively with cross functional teams, using Agile / DevOps principles to bring products to life, achieve business objectives and serve customer needs