Looks like you have JavaScript disabled. For the full Twine experience, you will need to re-enable it.

Hi, I’m Venkata Durga Kalyan Mukala, an AI/GenAI Engineer with 10+ years of experience delivering data science, ML, and Generative AI solutions across financial services, retail, telecom, semiconductor, and enterprise consulting environments. I design and implement end-to-end ML pipelines—from data ingestion and feature engineering to model development, deployment, and production monitoring—emphasizing reliability, explainability, and scalable cloud-native architectures. I thrive on collaborating with business stakeholders and engineering teams to turn complex data into practical AI solutions that drive measurable outcomes. In my work, I lead GenAI initiatives, build RAG-based document intelligence and knowledge-retrieval systems, and fine-tune LLMs with techniques like LoRA to improve relevance and grounding. I also establish robust MLOps/LLMOps practices, architect scalable cloud deployments (AWS/GCP/Azure), and develop secure, auditable AI solutions for regulated environments. I’m passionate about responsible AI, governance, and enabling teams with tools and workflows that accelerate innovation while maintaining governance and data security.…Hi, I’m Venkata Durga Kalyan Mukala, an AI/GenAI Engineer with 10+ years of experience delivering data science, ML, and Generative AI solutions across financial services, retail, telecom, semiconductor, and enterprise consulting environments. I design and implement end-to-end ML pipelines—from data ingestion and feature engineering to model development, deployment, and production monitoring—emphasizing reliability, explainability, and scalable cloud-native architectures. I thrive on collaborating with business stakeholders and engineering teams to turn complex data into practical AI solutions that drive measurable outcomes. In my work, I lead GenAI initiatives, build RAG-based document intelligence and knowledge-retrieval systems, and fine-tune LLMs with techniques like LoRA to improve relevance and grounding. I also establish robust MLOps/LLMOps practices, architect scalable cloud deployments (AWS/GCP/Azure), and develop secure, auditable AI solutions for regulated environments. I’m passionate about responsible AI, governance, and enabling teams with tools and workflows that accelerate innovation while maintaining governance and data security.

Venkata Durga Kalyan Mukala

AI Engineer, Data Scientist, Full Stack Developer, +2





Hi, I’m Venkata Durga Kalyan Mukala, an AI/GenAI Engineer with 10+ years of experience delivering data science, ML, and Generative AI solutions across financial services, retail, telecom, semiconductor, and enterprise consulting environments. I design and implement end-to-end ML pipelines—from data ingestion and feature engineering to model development, deployment, and production monitoring—emphasizing reliability, explainability, and scalable cloud-native architectures. I thrive on collaborating with business stakeholders and engineering teams to turn complex data into practical AI solutions that drive measurable outcomes. In my work, I lead GenAI initiatives, build RAG-based document intelligence and knowledge-retrieval systems, and fine-tune LLMs with techniques like LoRA to improve relevance and grounding. I also establish robust MLOps/LLMOps practices, architect scalable cloud deployments (AWS/GCP/Azure), and develop secure, auditable AI solutions for regulated environments. I’m passionate about responsible AI, governance, and enabling teams with tools and workflows that accelerate innovation while maintaining governance and data security.…Hi, I’m Venkata Durga Kalyan Mukala, an AI/GenAI Engineer with 10+ years of experience delivering data science, ML, and Generative AI solutions across financial services, retail, telecom, semiconductor, and enterprise consulting environments. I design and implement end-to-end ML pipelines—from data ingestion and feature engineering to model development, deployment, and production monitoring—emphasizing reliability, explainability, and scalable cloud-native architectures. I thrive on collaborating with business stakeholders and engineering teams to turn complex data into practical AI solutions that drive measurable outcomes. In my work, I lead GenAI initiatives, build RAG-based document intelligence and knowledge-retrieval systems, and fine-tune LLMs with techniques like LoRA to improve relevance and grounding. I also establish robust MLOps/LLMOps practices, architect scalable cloud deployments (AWS/GCP/Azure), and develop secure, auditable AI solutions for regulated environments. I’m passionate about responsible AI, governance, and enabling teams with tools and workflows that accelerate innovation while maintaining governance and data security.

Available to hire

Hi, I’m Venkata Durga Kalyan Mukala, an AI/GenAI Engineer with 10+ years of experience delivering data science, ML, and Generative AI solutions across financial services, retail, telecom, semiconductor, and enterprise consulting environments. I design and implement end-to-end ML pipelines—from data ingestion and feature engineering to model development, deployment, and production monitoring—emphasizing reliability, explainability, and scalable cloud-native architectures. I thrive on collaborating with business stakeholders and engineering teams to turn complex data into practical AI solutions that drive measurable outcomes.

In my work, I lead GenAI initiatives, build RAG-based document intelligence and knowledge-retrieval systems, and fine-tune LLMs with techniques like LoRA to improve relevance and grounding. I also establish robust MLOps/LLMOps practices, architect scalable cloud deployments (AWS/GCP/Azure), and develop secure, auditable AI solutions for regulated environments. I’m passionate about responsible AI, governance, and enabling teams with tools and workflows that accelerate innovation while maintaining governance and data security.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

GenAI/AI Engineer at Qualcomm

November 1, 2023 - Present

Led end-to-end GenAI platform design and deployment across cloud and edge environments. Partnered with Firmware and DSP engineering teams to build data pipelines for multimodal AI workloads, optimized ETL/SQL flows, and supported training/evaluation of on-device models. Implemented scalable Python-based services to integrate LLM inference, embedding generation, and telecom-domain AI models with internal platforms. Built and deployed retrieval-augmented generation (RAG) strategies, LangChain-based architectures, and vector-search pipelines for telecom docs, debugging aids, and chip-design knowledge retrieval. Architected multi-region, cloud-native GenAI infrastructure with robust MLOps/LLMOps (CI/CD, monitoring, cost governance). Led the development of LLM evaluation frameworks and automated experimentation pipelines, including A/B testing and grounded response validation. Implemented agentic AI workflows using LangGraph/LangChain and deployed Copilot-style automation and enterprise plu

Sr Data Science Engineer at Corning Credit Union

August 1, 2019 - October 1, 2023

Built end-to-end Python data pipelines (Pandas/NumPy/Scikit-learn) to standardize financial data from multiple systems for analytics, risk scoring, and loan performance. Developed predictive models for higher-risk loans, delinquencies, and fraud indicators with emphasis on interpretability. Implemented NLP solutions to organize and classify policy documents, and built Retrieval-Augmented Generation (RAG) pipelines to enable policy-backed Q&A from approved documents. Fine-tuned LLMs using LoRA for credit-union terminology and regulatory language. Deployed models on AWS with Dockerized APIs, implemented RBAC/data security controls, and monitored model quality through CloudWatch and BI dashboards. Designed prompt validation layers to ground responses to vetted financial documents and established end-to-end model lifecycle governance.

Sr Data Science Engineer at New York Life Insurance

September 1, 2016 - August 1, 2019

Processed policyholder, annuity, claims, and underwriting data to support segmentation, pricing, risk evaluation, and actuarial reporting. Built statistical models (mortality, lapse, claim likelihood) using Python (Pandas/NumPy/Scikit-learn) and maintained enterprise data models with ETL pipelines across policy, claims, CRM, and finance data sources. Automated risk scoring, lapse prediction, fraud detection, and retention analytics to strengthen underwriting. Modernized data pipelines and created Tableau/Excel dashboards for claims trends, agent performance, and policy profitability. Led data modeling and validation to support pricing and actuarial submissions, with governance over data quality and audit readiness.

Sr Data Science Engineer at Sam's Club

October 1, 2013 - August 1, 2016

Analyzed large-scale retail data (POS, membership, pricing, promotions) to support merchandising and operations decisions. Developed predictive models for demand forecasting, promotions effectiveness, and renewal/lapse risk, and built segmentation models for personalized offers. Created enterprise data models and ETL workflows integrating POS, CRM, and finance data into unified analytics. Delivered Tableau/Excel dashboards tracking sales, membership renewal, promotion lift, and store performance; collaborated with marketing, merchandising, supply chain, and finance to translate business questions into actionable insights.

Data Engineer at Accenture Solutions Private Ltd

June 1, 2012 - September 1, 2013

Translated business analytics requirements into technical specs; built automated Tableau dashboards and reporting systems for global clients. Implemented end-to-end ETL processes and data integration across ERP/CRM/data sources; designed OLTP/OLAP data models (Star/Snowflake schemas) to support real-time transactional and large-scale analytical workloads. Led metadata management, data quality checks, and versioning of dashboards and data pipelines. Collaborated in Agile environments to deliver dashboard enhancements and BI features, establishing a reusable framework for analytics delivery.