Suma Pyate Gouda Kake

Machine Learning Engineer

Hoffman Estates, Illinois, United States2 yrs 3 mos experience

AI ML PractitionerAI Enabled

Key Highlights

Expert in Generative AI and LLM systems.
Reduced manual effort by 95% in analytics.
Proven track record in scalable ML deployment.

Stackforce AI infers this person is a Machine Learning Engineer specializing in SaaS and Healthcare solutions.

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Skills

Core Skills

Generative Ai & Llm SystemsCloud-native Ml DeploymentData ScienceNlp & Applied Machine Learning

Other Skills

LangChainLangGraphOpenAI modelsMongoDBPythonFastAPIJava Spring BootReactJSAWSCI/CDRAGSQL ServerAmazon RedshiftTableauXGBoost

About

I’m a Machine Learning Engineer with 4+ years of experience building and deploying production-grade Generative AI and NLP systems. I specialize in designing Retrieval-Augmented Generation (RAG) pipelines, LLM orchestration (LangChain, LangGraph), and scalable ML microservices using Python, FastAPI, and AWS. My work focuses on taking AI solutions from concept to production, with an emphasis on accuracy, scalability, and real business impact. Currently, I work on enterprise GenAI platforms used across multiple business units, enabling real-time document intelligence, contextual chatbots, and automated knowledge retrieval. Previously at IQVIA, I developed predictive ML models and automated analytics pipelines that reduced manual effort by 95% and significantly improved campaign targeting effectiveness. Core strengths: • Generative AI & LLM systems (RAG, prompt optimization, vector search) • NLP & applied machine learning • Cloud-native ML deployment (AWS, CI/CD, microservices) • End-to-end ML lifecycle ownership I’m actively seeking Machine Learning Engineer, GenAI Engineer, or Applied Scientist roles in product-driven teams where I can build scalable AI systems and solve real-world problems. 📍 Dallas, TX | Open to relocation | Authorized to work in the US

Experience

2 yrs 3 mos

Total Experience

2 yrs 3 mos

Average Tenure

Current Experience

Johnson controls

AI/ML Engineer

Jan 2024 – Present · 2 yrs 4 mos · Chicago, Illinois, United States · Remote

Designed and developed a Generative AI-based web application integrating LangChain, LangGraph, OpenAI models, and MongoDB Vector Store for real-time document retrieval and context-aware chatbot responses.
Architected RAG-based LLM pipelines enabling hybrid retrieval of structured and unstructured content, enhancing chatbot's accuracy and contextual relevance.
Implemented advanced contextual retrieval logic to search for answers based on user queries, using prompt augmentation with relevant documents retrieved via vector similarity.
Introduced vector filtering capabilities to apply search filters (e.g., document tags or source types) while generating responses, ensuring more targeted and relevant output.
Engineered Python FastAPI microservices to generate embeddings, perform similarity search, manage knowledge bases, and dynamically query vector stores.
Developed secure, scalable Java Spring Boot services for user registration, JWT-based authentication, chat history management, and integration with AI services.
Built modular, responsive ReactJS frontend for user interaction, document upload, and chatbot communication.
Implemented real-time monitoring, logging, and alerting frameworks across Python, Java, and React layers to ensure high system uptime and reliability.
Enhanced chatbot memory and long-context handling using advanced LangChain memory modules.
Designed flexible API endpoints to support multi-modal document ingestion including PDFs, Word docs, and plain text.
Deployed AI infrastructure on AWS EC2 instances with Launch Templates, Auto Scaling Groups, Load Balancers, and Route 53.
Configured CI/CD pipelines via GitHub Actions for seamless deployment and rollback automation.
Established SSH key-based secure deployments and Elastic IP management for consistent service access.
Achieved 85%+ code coverage using JaCoCo and Jest, ensuring robust unit testing for both backend and frontend components.

LangChainLangGraphOpenAI modelsMongoDBPythonFastAPI+6

Iqvia

Data Scientist

Sep 2020 – Dec 2022 · 2 yrs 3 mos · Bengaluru, Karnataka, India

Analyzed and processed multi-channel campaign data for pharmaceutical agencies targeting healthcare providers (HCPs). Campaign data received through FTP servers, included engagement metrics for channels such as email, display banners, and direct mail, with NPI (National Provider Identifier) serving as the primary key.
Automated the extraction and loading of channel-specific campaign data from FTP servers into SQL Server and Amazon Redshift.
Developed Tableau dashboards connected to Amazon Redshift to present key metrics, enabling stakeholders to monitor campaign performance across multiple channels.
Built logistic regression models in Python to predict engagement probabilities (e.g., email opens, banner impressions), helping optimize campaign strategies for pharmaceutical clients.
Developed a ReactJS dashboard to display key performance metrics of multi-channel campaign data, providing real-time insights into marketing effectiveness.
Created modular ReactJS components to display email campaign data, banner impressions, and direct mail responses, improving component reusability.
Implemented dynamic data filtering and sorting features using React hooks, allowing users to customize views based on campaign performance metrics.
Designed protected routes using useContext and React Router to restrict component access based on user roles (Admin, Client, and Visitor), enhancing security and role-based access control.
Created a component allowing users to display HTML reports dynamically and download them based on applied filters, ensuring customized reporting and better data accessibility.
Optimized API calls using Axios and implemented lazy loading to improve performance, reducing the initial load time.
Developed unit test cases for ReactJS components using Jest and React Testing Library, improving code reliability and maintainability.