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

I'm an AI/ML Engineer and Data Scientist with 4+ years of experience designing, deploying, and optimizing data-driven solutions across large-scale cloud environments. I specialize in machine learning, generative AI, big data engineering, and MLOps, with hands-on expertise in Python, PySpark, Databricks, AWS SageMaker, and Kubernetes. I have built LLM-powered applications, predictive models, and automated data pipelines that accelerate business insights, reduce operational costs, and enhance decision-making. I enjoy collaborating with cross-functional teams to deliver scalable, ethical AI solutions that align with organizational goals. I’m passionate about turning data into actionable insights and championing responsible AI practices. I engage stakeholders to translate analytical findings into practical strategies, ensure transparency and compliance, and continuously optimize models and pipelines across cloud platforms for measurable business impact.…I'm an AI/ML Engineer and Data Scientist with 4+ years of experience designing, deploying, and optimizing data-driven solutions across large-scale cloud environments. I specialize in machine learning, generative AI, big data engineering, and MLOps, with hands-on expertise in Python, PySpark, Databricks, AWS SageMaker, and Kubernetes. I have built LLM-powered applications, predictive models, and automated data pipelines that accelerate business insights, reduce operational costs, and enhance decision-making. I enjoy collaborating with cross-functional teams to deliver scalable, ethical AI solutions that align with organizational goals. I’m passionate about turning data into actionable insights and championing responsible AI practices. I engage stakeholders to translate analytical findings into practical strategies, ensure transparency and compliance, and continuously optimize models and pipelines across cloud platforms for measurable business impact.

Vennela Billa

Data Scientist, AI Engineer, AI Developer, +5





I'm an AI/ML Engineer and Data Scientist with 4+ years of experience designing, deploying, and optimizing data-driven solutions across large-scale cloud environments. I specialize in machine learning, generative AI, big data engineering, and MLOps, with hands-on expertise in Python, PySpark, Databricks, AWS SageMaker, and Kubernetes. I have built LLM-powered applications, predictive models, and automated data pipelines that accelerate business insights, reduce operational costs, and enhance decision-making. I enjoy collaborating with cross-functional teams to deliver scalable, ethical AI solutions that align with organizational goals. I’m passionate about turning data into actionable insights and championing responsible AI practices. I engage stakeholders to translate analytical findings into practical strategies, ensure transparency and compliance, and continuously optimize models and pipelines across cloud platforms for measurable business impact.…I'm an AI/ML Engineer and Data Scientist with 4+ years of experience designing, deploying, and optimizing data-driven solutions across large-scale cloud environments. I specialize in machine learning, generative AI, big data engineering, and MLOps, with hands-on expertise in Python, PySpark, Databricks, AWS SageMaker, and Kubernetes. I have built LLM-powered applications, predictive models, and automated data pipelines that accelerate business insights, reduce operational costs, and enhance decision-making. I enjoy collaborating with cross-functional teams to deliver scalable, ethical AI solutions that align with organizational goals. I’m passionate about turning data into actionable insights and championing responsible AI practices. I engage stakeholders to translate analytical findings into practical strategies, ensure transparency and compliance, and continuously optimize models and pipelines across cloud platforms for measurable business impact.

Available to hire

I’m an AI/ML Engineer and Data Scientist with 4+ years of experience designing, deploying, and optimizing data-driven solutions across large-scale cloud environments. I specialize in machine learning, generative AI, big data engineering, and MLOps, with hands-on expertise in Python, PySpark, Databricks, AWS SageMaker, and Kubernetes. I have built LLM-powered applications, predictive models, and automated data pipelines that accelerate business insights, reduce operational costs, and enhance decision-making. I enjoy collaborating with cross-functional teams to deliver scalable, ethical AI solutions that align with organizational goals.

I’m passionate about turning data into actionable insights and championing responsible AI practices. I engage stakeholders to translate analytical findings into practical strategies, ensure transparency and compliance, and continuously optimize models and pipelines across cloud platforms for measurable business impact.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

AI/ML Engineer at Databricks

June 2, 2023 - November 25, 2025

Designed and deployed large-scale ML models on the Databricks Lakehouse using Python, PySpark, Delta Lake, and MLflow, reducing training time by 30% and improving model reproducibility. Built Generative AI and RAG pipelines with LangChain, Pinecone, and LLM APIs to enable enterprise knowledge retrieval, cutting manual research time by 35%. Optimized distributed GPU training workflows with Spark MLlib and MosaicML to achieve 25% faster convergence and better resource utilization. Implemented end-to-end MLOps pipelines with GitHub Actions, Docker, and Kubernetes to automate CI/CD for model deployments, shortening release cycles from 2 weeks to 5 days. Established model monitoring and governance using MLflow, Prometheus, and Databricks Model Registry to ensure drift detection, versioning, and adherence to ethical AI practices. Collaborated with data engineers, product teams, and business stakeholders to align AI/ML solutions with strategic goals and drive platform adoption.

Data Scientist at HCLTech

April 30, 2022 - April 30, 2022

Developed and deployed predictive and statistical models using Python, Scikit-learn, TensorFlow, and XGBoost, improving fraud detection and demand forecasting accuracy by 20%. Designed and maintained ETL and data processing pipelines with Airflow, PySpark, and SQL, automating ingestion of 1M+ daily records and reducing processing time by 40%. Conducted EDA and feature engineering to uncover insights, optimize data quality, and enhance model interpretability for key business use cases. Leveraged AWS SageMaker and Kubernetes to operationalize data science models, enabling real-time scoring for over 100K API requests per day with sub-200ms latency. Created interactive dashboards and data visualizations in Power BI and Plotly, translating model outputs into actionable insights for business stakeholders. Partnered with cross-functional teams to translate analytical findings into data-driven strategies, driving 15% cost reduction and improving decision-making efficiency. Collaborated with co

Data Scientist at HCLTech

July 1, 2020 - April 1, 2022

Developed and deployed predictive and statistical models using Python, Scikit-learn, TensorFlow, and XGBoost, improving fraud detection and demand forecasting accuracy by 20%. Designed and maintained ETL and data processing pipelines with Airflow, PySpark, and SQL, automating ingestion of 1M+ daily records and reducing processing time by 40%. Conducted EDA and feature engineering to uncover insights, optimize data quality, and enhance model interpretability for key business use cases. Leveraged AWS SageMaker and Kubernetes to operationalize data science models, enabling real-time scoring for over 100K+ API requests per day with sub-200ms latency. Created interactive dashboards and data visualizations in Power BI and Plotly, translating model outputs into actionable insights for business stakeholders. Partnered with cross-functional teams to translate analytical findings into data-driven strategies, driving 15% cost reduction and improving decision-making efficiency. Collaborated with c