Akshay Kumar C P

Machine Learning Engineer (Senior Consultant)

(Second company)

Summary

• Involve and contribute technical components to RFP proposal's
• Map business requirements to data science problem statement, design & implement solution.
• Develop Generative AI/AI solution using Azure cloud.
• Communicate with multiple stakeholders and give demo's.

Project's

Generative AI Contract Validation

• Validate contract documents against compliance rules and perform criticality assessment.
• Activities performed: Prompt Engineering | RAG | Deployment.
• Tech Stack: Azure services ( OpenAI | AI search | ML workspace | Storage | Key vault ) Langchain, etc.
• 60% high confidence criticality assessment.
• 1.4 M€ / year cost avoidance.

Generative AI Chatbot

• Utilized open source LLM due to constrain on not utilizing APIs
• Activities performed: Prompt Engineering | RAG | Deployment.
• Tech Stack: HuggingFace LLM models such as mistral, llama 2, etc. , Quantization, Chroma vector DB, Langchain, Ollama etc.

Generate Synthetic Data using Generative AI

• Tabular: Utilized libraries such as CTGAN, SDV, etc for generation.
• Images: Generative models such as GAN, BIG-GAN, stable diffusion, etc.
• Text: Used GPT-2, Mosiacml, Bloom, falcon, etc. for text generation tasks.
• Implemented using Hugging Face, TensorFlow Hub and other frameworks.

Natural Language to SQL

• Implemented using Open AI “text-davinci-003” model.
• Built UI using Gradio framework for quick demo.

Customer Satisfaction Analytics

• Research & analysis on requirements and planning.
• Brainstorming the solution with respect to requirements.
• Generating actionable insights from data and creating reports, presentation and dashboards to take key business decision.
• Perform analysis namely predicting loyal customers using cluster models, CSAT, NPS, SERVQUAL, Recency Frequency Monetary (RFM), Cohort analysis.
• Use python for automation (OOPS, REST APIs, logging, exceptional handling, config file. linting, etc.).
• Machine Learning models such as clustering, ordinal regression stats model for predictive models.

AWS Clean Room

• Executed using AWS Clean Room Service.
• Configured collaboration between advertiser and publisher using, S3 and Glue.
• Showcased taking marketing decisions in the world without third party cookies.

Amperity

• Setup and execute Identity Resolution (IDR) and customer campaigns using Amperity platform.

Hackathon

Insect Acoustic AI

• Is a Multi class audio classification. Extracted features from audio data and experiment with multiple model architectures such as ANN, Hugging Face pretrained models and fine tuning.
• Experimentation was performed on cloud AWS Sage maker.
• Evaluation metrics such as True Positive, Accuracy, etc.

Google Generative AI

• Theme: Customer products and retail: Personalized Copy Generate.
• Used Google's LLM "text-bison (latest)" model from Google Vertex AI .
• Personalized content generation for e-commerce platform such as:
• Create product description for new/existing products.
• Personalized content generation for promotional activities (SMS/Email/Social media) based on customer past transaction details.
• Come up with strategies for retaining churning customers.

Software Development Engineer - Machine Learning

(First company)

Design & Implement multiple data science products from requirements phase to deployment phase.

With multiple data science products, reduced manual intervention, implemented automation and increased solution accuracy from 35% to 55%.

Debug product and provide fix for customer issues.

Project's

Open-Source License Detection

• Developed using Python, NLP, ML, REST APIs, UWSGI Server & MongoDB.
• Increased component license mappings from 35% to 55%.
• Handled data preprocessing, modelling, expose model prediction using REST API, deployment & maintenance.

Copyright Extraction from License Text

• Performed entities annotation using “ner-annotator” tool on license text dataset.
• Built using Python, NLP, Spacy NER, REST APIs, UWSGI Server & MongoDB.
• Product was benefitted by identifying the precise copyright holder from license text.

Q&A Chatbot for HR

• Implemented using Python, Rasa X & MongoDB.
• Chatbot answered FAQ on HR department and sends out the information to mail.
• HR department load was reduced as most of the Q & A was answered by Q&A Chatbot.

Automation Tools, Python automation projects.

• Rules for identifying components.
• Download, extract important information from releases of component.
• Validate URL of component.
• Generate SQL queries, etc.

Web Developer Intern

Podcasting operational change management inside of workflows to establish a framework.

Taking seamless key performance indicators offline to maximise the long tail.

Keeping your eye on the ball while performing a deep dive on the start-up mentality to derive convergence on cross-platform integration.

Master Of Computer Application (MCA)

CGPA: 7.91