AI/ML Engineer

AKHIL ADE

Dallas, TX 469-***-****

**********@*****.***

PROFESSIONAL SUMMARY

●AI Engineer and Data Scientist with 5+ years of experience delivering scalable AI and data solutions across automotive, industrial, and research domains.

●Proven expertise in developing end-to-end machine learning pipelines, fine-tuning Large Language Models (LLMs), and applying GenAI for real-world automation and insight generation.

●Adept at sensor fusion for ADAS, data standardization, and deploying intelligent agents to extract actionable insights from tabular and unstructured data.

●Demonstrated ability to reduce manual workloads by up to 70%, improve model performance by over 25%, and deliver multilingual content automation.

●Strong foundation in computer vision, natural language processing, and containerized deployments using tools like PySpark, Docker, Azure AI Foundry, and Hugging Face.

●Passionate about building practical AI systems that improve efficiency, decision-making, and accessibility.

EXPERIENCE

Cigna AI/Ml Engineer Dallas, TX May 2024 –

Present Responsibilities:

Successfully deployed Transformer-based models, including GPT variants, in production using TensorFlow Serving and Flask, enabling real-time inference and seamless integration into applications.

Applied fine-tuned GPT models for natural language understanding (NLU) tasks such as sentiment analysis, text classification, and question answering, showcasing the power of pre-trained language models in real-world scenarios.

Designed and implemented conditional GANs (cGANs) for tasks like conditional image generation, text-to-image synthesis, and image-to-image translation, enabling controlled content generation.

Leveraged transfer learning and pre-trained Keras models to accelerate GenAI model development and achieve state-of-the-art performance with limited data.

Fine-tuned Named Entity Recognition (NER) models using Transformers and spaCy, customizing them for domain- specific terminology and enhancing entity extraction accuracy.

Explored semantic relationships in large text corpora using word embedding visualizations and t-SNE, facilitating better understanding of language models.

Implemented custom layers and loss functions in MXNet to support advanced generative architectures tailored to domain needs.

Conducted hyperparameter tuning and optimization experiments using Optuna and Ray Tune for generative model performance maximization.

Applied feature engineering and n-gram techniques to improve the granularity of sentiment detection in text-based GenAI applications.

Implemented convolutional and recurrent neural networks (CNNs and RNNs) in Keras for generative tasks involving sequential and spatial data.

Developed scripts using Scikit-learn, Transformers, spaCy, and TensorFlow to streamline data preprocessing and model training pipelines in generative NLP workflows.

Explored edge AI deployments for GenAI inference, incorporating hardware acceleration (GPU, FPGA) and on- device model execution with attention to privacy and latency.

Maintained collaborative and scalable GenAI development using Git and modern MLOps practices.

Environment :GPT (including fine-tuned GPT models), OpenAI, TensorFlow, TensorFlow Serving, PyTorch, Scikit-learn, Auto-Sklearn, H2O.ai, MXNet, Keras, Transformers (Hugging Face), spaCy, Optuna, Ray Tune, Flask, FastAPI, Git, AWS (EC2, S3), Edge AI (FPGA, GPU, ASIC), CNN, RNN (LSTM, GRU), cGANs, NLP, Time Series Forecasting, Anomaly Detection, Transfer Learning, Feature Engineering, Model Interpretability, Hyperparameter Tuning, Deep Learning, Generative AI (GANs, cGANs), MLOps, Version Control, Jupyter Notebook, PyCharm, RStudio, Data Visualization (t-SNE), Real-time Inference, Model Deployment, Edge Computing.

Walmart AI/Ml Engineer CA January 2023 – May 2024 Responsibilities:

Integrated AI solutions using statistical modelling, decision trees, and sentiment analysis to optimize model accuracy.

Conducted A/B testing for multivariate analysis on gaming product promotions, assessing the impact of combo offers on sales.

Leveraged AWS Bedrock to build and deploy generative AI models, streamlining AI adoption for business applications.

Utilized AWS OpenSearch for efficient indexing and searching, improving query performance and data retrieval."

Created a chatbot using GPT-3 to enhance customer support, resulting in a 30% reduction in response time.

Managed vector databases to improve storage efficiency and boost query performance by 35%.

Designed augmented reality engines with Bayesian models, SVMs, CRFs, and other generative techniques.

Applied prompt engineering for generative AI in data synthesis, image creation, and video augmentation.

Utilized NLP libraries such as NLTK, SpaCy, and Gensim for text pre-processing, classification, and tagging.

Built machine learning pipelines in TensorFlow, Scikit-Learn, and PyTorch, and implemented predictive models for various applications.

Deployed LLM-based applications to automate business processes and improve customer engagement with OpenAI GPT.

Developed interactive Power BI dashboards, enhancing data visualizations and transitioning Excel datasets to improve reporting.

Analyzed data and performed data preparation by applying historical model on the data set in AZURE ML

Created RESTful services using FastAPI, integrated with PostgreSQL, DynamoDB, and S3 for robust data handling.

Designed MLOps pipelines using Vertex AI for CI/CD, streamlining deployment and model integration in production.

Leveraged GANs and VAEs for generative AI applications, specializing in realistic image and data synthesis.

Developed deep learning projects using CNNs and RNNs, including movie recommendation systems and stock price predictions.

Utilized ETL tools (e.g., Apache NiFi, Talend, AWS Glue) to integrate disparate data sources, enabling seamless data flow and accessibility for analysis.

Applied LLM research to enhance NLP algorithms, including language quality evaluations.

Built Keras-based computer vision models for image classification using 5-fold cross-validation.

Proficient in using Python and R for model customization and generative AI applications, including language generation for marketing content.

Conducted research on language models, developing generative AI experiences with Google Vertex AI and employed RAG techniques for enhanced data analysis.

Enhanced AI applications using AWS services like EC2, S3, Lambda, and RDS to deploy scalable solutions.

Conducted data manipulation, slicing, and statistical testing using Pandas, NumPy, and Scikit-Learn.

Experienced in building predictive models and using machine learning algorithms for key metric forecasting.

Built AI-driven cognitive search solutions to improve data retrieval accuracy.

Skilled in IDEs like Eclipse, PyCharm, XCode, and Sublime Text for Python-based development.

Developed LSTM-based review analysis systems with TF-IDF, Word2Vec, and other NLP techniques.

Deployed generative AI applications for content creation, translation, and analytics, including custom workflows in Python and R.

Conducted LLM research and developed advanced NLP algorithms to enhance automated data processing.

Built predictive analytics models using AI for insights across customer and business processes.

Collaborated on computer vision projects, implementing Keras models for image classification and object detection.

Environment: GPT-3, OpenAI, TensorFlow, Scikit-Learn, PyTorch, Vertex AI, AWS (EC2, S3, Lambda, RDS), Azure, Power BI, FastAPI, PostgreSQL, DynamoDB, Keras, IDEs (Eclipse, PyCharm, XCode, Sublime), A/B Testing, ML Pipelines, Predictive Modeling, NLP, Deep Learning (CNN, RNN), Generative AI (GANs, VAEs), MLOps, Data Manipulation, Cognitive Search.

Tata Consultancy Services/ Airtable AI/ML Developer India Apr 2021 - June 2022 Responsibilities:

Updated an existing real time bidding platform (RTB) to conform to Open RTB standards. Platform written in Python with Tornado, backed by Redis.

Developed a media proxy server managed through a central service. Included usage reporting and URL/Domain blacklisting. Written in Python, using Tornado and PyPy, with a Django dashboard.

Developed tools using Python, Shell scripting, XML to automate some of the menial tasks.

Worked as dev-ops create deployment strategy and scripts (BASH/Python).

Created and populated digital brochures using PageTurnPro and built photo galleries on website in the Django CMS and also using Django CMS plugin.

Experience using Content Management Systems: WordPress and Django CMS plugins.

Supported/maintained client website within the DJANGO CMS system for various website needs.

Handled caching in Ruby on Rails using RubyGems, Rails gems, ORM.

Used Pandas library for statistical Analysis.

Reviewed feedback about the debugging issues, fixed bugs with HTML, JavaScript codes.

Developed test scripts for puppet modules using ruby framework, planned and developed TDD scripts.

Used Bootstrap and Angular and Bootstrap for creating rich, Responsive UI Screens for varying screen sizes and devices.

Constructed web pages for application using MVC3, Java Script, JQuery.

Designed and implemented restful services security proxy using Spring Boot, and JSON Web Token to provide secure API access to user.

Configured authentication mechanisms including SAML-based single sign on (SSO) and LDAP.

In this application pyramid appengine provides a project skeleton for running Pyramid on Google App Engine.

Used Vaadin framework to build single page web UI for java application.

Migrated the production MySQL schema to the new AWS RDS Aurora instance.

Used Groovy scripting for OSC and SOAP UI /Ready API for performance testing.

Worked on IDE's like Netbeans and version control tools like Mercurial.

Developed a POC for reading Bloomberg NewsFeed dataCMS team using primarily Core Java, CoreMedia9 and Spring Restful WebServices, Java/WebSphere.

Used SVN version controller to manage code versions and to check in the data as XML files.

Created test coverage for the web services by using Junit and Easymock.

Build a Scrum framework based on SAFe. Migrated process framework from Waterfall.

Created AWS EC2 Linux instances and BASH scripts to run post processing. Used Jenkins to run the deployment process.

Implemented AWS solutions using S3.

Automated software build processes, similar to tools like Make or Gradle using Ant.

Integrated Jira and Confluence into splunk enterprise.

Made heavy use of UNIX-style regular expressions within Pegasystems toolset.

Helped in integrating Crucible into Jira and HipChat.

Environment: Python, Django, ORM, pandas, Tornado, JavaScript, HTML5, CSS3, Ruby, ROR Ruby on Rails, bootstrap, jQuery, JSON, web token, SSO/SAML, Pyramid, Java, MySQL, Rest, Soap, Netbeans, Websphere, CVS, SVN, Junit, Waterfall, AWS, EC2, S3, Ant, XML, Jira, Unix, hipchat.

Indus Infotech Python Developer India May 2019 - March 2021 Responsibilities:

Built website and database system for in house, programmed in Python through Django streamline framework.

Responsible for Coding using Python, Django, JavaScript, CSS, HTML and XML.

Designed and styled UI screens using HTML, JavaScript and CSS.

Developed client-side AJAX application that uses JavaScript OOP and more Bind objects and retrieve them via JNDI interface.

Wrote complex SQL queries, stored procedures in PL/SQL.

Developed WebServices for interacting with Backend. Designed Solutions using Hibernate and JPA to interface with the relational database.

Developed and designed Software Engineering Solutions using Agile Methodology.

Involved in design, development and support phases of SDLC.

Environment: Python, Django, JSP, HTML, CSS, JQuery, Struts, EJB, PL/SQL, MYSQL, JIRA UNIX, CVS, ANT, web services, UNIX Linux, and Windows.

EDUCATION

Master of Science in Computer & Information Sciences

●University of Texas at Arlington Arlington, TX, USA

TECHNICAL SKILLS

●Programming Languages: Python, Java, C/C++

●AI/ML Frameworks: TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers, Azure AI Foundry, Langchain

●Generative AI & Large Language Models: OpenAI GPT-4, Claude, LLaMA, LangChain, AutoGPT

●Machine Learning & Deep Learning: CNN, LLMs, BERT, T5, Feature Engineering, Model Fine-tuning, Prompting

●Data Engineering & Big Data: PySpark, ETL Pipelines, AWS Lambda, REST APIs

●Data Science & Analytics: Anomaly Detection, Predictive Maintenance, Object Detection, Sensor Fusion

●Computer Vision: ADAS, LIDAR, RADAR, Image Processing, Containerized Pipelines (Docker)

●Knowledge Graphs & Agents: Neo4j, SmolAgents, Agent-based Systems, Multi-modal AI

●Performance Optimization: GPU Acceleration (CUDA, OpenCL)

●Version Control & Collaboration: Git, GitHub

●Automation & Deployment: CI/CD Pipelines, Containerization (Docker), Automation Scripts, Jinja Templates

PUBLICATIONS

●Career Recommendation using ANN – International Journal for Research in Applied Science & Engineering Technology This paper, developed under the guidance of Dr. K. Kranthi Kumar, proposes an Artificial Neural Network (ANN)-based career recommendation system

CERTIFICATIONS

●AWS Certified Cloud Practitioner February 2024

●Microsoft Certified: Azure Fundamentals March 2022

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