Python Job: AI-Machine Learning Developer

• Lead brainstorming sessions to develop potential solutions for business needs or problems
• Provide specifications according to which the solution is defined, managed, and delivered
• Identify opportunities for process improvements
• Define features, development phases, and solution requirements.
• Supervised, Unsupervised and reinforcement learning Using Python
• Set-up, maintenance, and ongoing development of continuous build/ integration infrastructure (CI/CD)
• Experience with different NoSQL and SQL, graph databases
• Image and Audio Classification with TensorFlow, scikit-learn
• Configuration of Watson Explorer crawl and Watson AppBuilder development using XSLT and Ruby
• Entity Extraction from unstructured data like PDF
• Text Similarities and Summarization with Python
• Image processing with Open-CV, Pillow
• Classification Model training with TensorFlow
• Design Analytics dashboard with Power BI and create CI/CD pipeline with MS flow
• Created custom ML models and hosted on AWS, Azure or IBM Watson
• Used different AI/ML services like AWS Sagemaker, Azure ML, Watson Studio, Watson Knowledge Studio
• Smart Document Understanding with IBM Watson
• Power shell programming for monitoring server resources
• Metadata extraction from scanned PDF
• Managing project Constraints, Dependencies & Issues.
• Conducted system test for interfaces and component programs
• Assisted in UAT and prepared go-live readiness
• Proof of concept for different AI use cases
• Prepare and document testing requirements.
• Monitoring of IBM Watson cloud usage

Job Types: Full-time, Permanent

Pay: $120,000.00 – $150,000.00 per year

Benefits:

• Employee stock purchase plan
• Health insurance
• Profit sharing

Schedule:

• 8 hour shift

Experience:

• Python: 5 years (Preferred)
• continuous build/ integration infrastructure (CI/CD): 5 years (Preferred)
• Machine Learning: 5 years (Preferred)
• NoSQL and SQL: 5 years (Preferred)
• AI/ML services: 4 years (Preferred)
• IBM Watson cloud: 2 years (Preferred)

Work Location: In person