1. Be a hands on problem solver with consultative approach, who can apply Machine Learning & Deep Learning algorithms to solve business challenges

• Use the knowledge of wide variety of AI/ML techniques and algorithms to find what combinations of these techniques can best solve the problem
• Improve Model accuracy to deliver greater business impact
• Estimate business impact due to deployment of model

2. Work with the domain/customer teams to understand business context , data dictionaries and apply relevant Deep Learning solution for the given business challenge

3. Working with tools and scripts for sufficiently pre-processing the data & feature engineering for model development Python / R / SQL / Cloud data pipelines

4. Design , develop & deploy Deep learning models using Tensorflow / Pytorch

5. Experience in using Deep learning models with text, speech, image and video data

• Design & Develop NLP models for Text Classification, Custom Entity Recognition, Relationship extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, Semantic Search using NLP tools like Spacy and opensource Tensorflow, Pytorch, etc
• Design and develop Image recognition & video analysis models using Deep learning algorithms and open source tools like OpenCV
• Knowledge of State of the art Deep learning algorithms

6. Optimize and tune Deep Learnings model for best possible accuracy

7. Use visualization tools/modules to be able to explore and analyze

outcomes & for Model validation eg: using Power BI / Tableau

8. Work with application teams, in deploying models on cloud as a service or on-prem

• Deployment of models in Test / Control framework for tracking
• Build CI/CD pipelines for ML model deployment

9. Integrating AI&ML models with other applications using REST APIs and other connector technologies

10. Constantly upskill and update with the latest techniques and best practices. Write white papers and create demonstrable assets to summarize the AIML work and its impact.

• Technology/Subject Matter Expertise
• Sufficient expertise in machine learning, mathematical and statistical sciences
• Use of versioning & Collaborative tools like Git / Github
• Good understanding of landscape of AI solutions cloud, GPU based compute, data security and privacy, API gateways, microservices based architecture, big data ingestion, storage and processing, CUDA Programming
• Develop prototype level ideas into a solution that can scale to industrial grade strength
  • Ability to quantify & estimate the impact of ML models