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I am a results-driven ML/MLOps engineer with over 3 years of experience in translating research prototypes into production-grade, CI/CD-driven ML systems. I have expertise in Python, PyTorch/TensorFlow, Docker/Kubernetes, Jenkins/GitLab CI, and Infrastructure as Code tools like Terraform and Ansible. My work includes reducing inference latency, automating regression pipelines, and deploying reliable, monitored models across scalable cloud and containerized environments. I am adept at aligning machine learning solutions with performance and operational goals collaborating with infrastructure teams. I enjoy mentoring teams, engineering automated evaluation engines, and building MLOps pipelines to streamline production workflows that improve deployment speed and model robustness across multiple industries including healthcare, retail, and customer analytics.…I am a results-driven ML/MLOps engineer with over 3 years of experience in translating research prototypes into production-grade, CI/CD-driven ML systems. I have expertise in Python, PyTorch/TensorFlow, Docker/Kubernetes, Jenkins/GitLab CI, and Infrastructure as Code tools like Terraform and Ansible. My work includes reducing inference latency, automating regression pipelines, and deploying reliable, monitored models across scalable cloud and containerized environments. I am adept at aligning machine learning solutions with performance and operational goals collaborating with infrastructure teams. I enjoy mentoring teams, engineering automated evaluation engines, and building MLOps pipelines to streamline production workflows that improve deployment speed and model robustness across multiple industries including healthcare, retail, and customer analytics.

Tharun Chowdarya Malepati

AI Engineer, Developer, Data Scientist, +1

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I am a results-driven ML/MLOps engineer with over 3 years of experience in translating research prototypes into production-grade, CI/CD-driven ML systems. I have expertise in Python, PyTorch/TensorFlow, Docker/Kubernetes, Jenkins/GitLab CI, and Infrastructure as Code tools like Terraform and Ansible. My work includes reducing inference latency, automating regression pipelines, and deploying reliable, monitored models across scalable cloud and containerized environments. I am adept at aligning machine learning solutions with performance and operational goals collaborating with infrastructure teams. I enjoy mentoring teams, engineering automated evaluation engines, and building MLOps pipelines to streamline production workflows that improve deployment speed and model robustness across multiple industries including healthcare, retail, and customer analytics.…I am a results-driven ML/MLOps engineer with over 3 years of experience in translating research prototypes into production-grade, CI/CD-driven ML systems. I have expertise in Python, PyTorch/TensorFlow, Docker/Kubernetes, Jenkins/GitLab CI, and Infrastructure as Code tools like Terraform and Ansible. My work includes reducing inference latency, automating regression pipelines, and deploying reliable, monitored models across scalable cloud and containerized environments. I am adept at aligning machine learning solutions with performance and operational goals collaborating with infrastructure teams. I enjoy mentoring teams, engineering automated evaluation engines, and building MLOps pipelines to streamline production workflows that improve deployment speed and model robustness across multiple industries including healthcare, retail, and customer analytics.

Available to hire

I am a results-driven ML/MLOps engineer with over 3 years of experience in translating research prototypes into production-grade, CI/CD-driven ML systems. I have expertise in Python, PyTorch/TensorFlow, Docker/Kubernetes, Jenkins/GitLab CI, and Infrastructure as Code tools like Terraform and Ansible. My work includes reducing inference latency, automating regression pipelines, and deploying reliable, monitored models across scalable cloud and containerized environments.

I am adept at aligning machine learning solutions with performance and operational goals collaborating with infrastructure teams. I enjoy mentoring teams, engineering automated evaluation engines, and building MLOps pipelines to streamline production workflows that improve deployment speed and model robustness across multiple industries including healthcare, retail, and customer analytics.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Javanese

Intermediate

Work Experience

Machine Learning Engineer at Cyrvana, USA

July 1, 2024 - Present

Developed and deployed deep learning models for customer sentiment analysis using BERT and SpaCy, improving feedback classification accuracy by 32%. Created real-time object detection system using YOLOv5 and OpenCV for retail automation. Deployed scalable ML models using AWS SageMaker, reducing prediction latency by 35% and improving inference reliability. Improved customer churn prediction accuracy by 18% through feature engineering and hyperparameter tuning. Built MLOps pipelines for model retraining, version control, and deployment using MLflow and GitHub Actions. Developed NLP models using Transformers and deployed via Dockerized APIs. Automated ETL pipelines using Python and Airflow, saving over 20 hours per week in manual reporting. Built RESTful APIs with Flask and containerized applications using Docker. Collaborated with data engineering team to automate data pipeline, reducing model retraining time by 45%.

Machine Learning Engineer at Techimax, India

December 31, 2022 - July 17, 2025

Led the development of a recommendation system using collaborative filtering, increasing user engagement by 25%. Implemented NLP pipelines for resume parsing and keyword extraction for an HR tech client. Used MLflow for model tracking and versioning, ensuring reproducibility and streamlined deployment. Optimized training time and inference speed on large datasets using GPU acceleration on AWS EC2.

Generative AI Engineer | Founder's Team Member at Observo

June 1, 2025 - Present

Directed a 6-intern GenAI metrics squad mentoring them in RAG pipelines and prompt engineering to improve collaboration across product, ML, and DevOps teams. Engineered an automated evaluation engine that reduced model-release checkpoints by 50% and doubled deployment speed using Python and CI/CD practices. Reverse-engineered 45 rival metrics and distilled a core 15-metric kit using Python, LangChain, FAISS, and LLaMA-3, establishing platform standards and cohesive end-to-end deployment. Authored an LLM-as-Judge prompt suite and created a 50-case ground-truth dataset, increasing hallucination detection recall by 18 percentage points and integrated Grafana dashboards via GitHub Actions CI/CD for continuous monitoring.

Machine Learning Engineer at Cyrvana

July 1, 2024 - Present

Developed and deployed deep learning models for customer sentiment analysis using BERT and SpaCy, improving classification accuracy by 32%. Created a real-time object detection system using YOLOv5 and OpenCV for retail automation, enhancing inventory management. Deployed scalable ML models with AWS SageMaker reducing prediction latency by 35% and improving inference reliability with CI/CD integration. Improved churn prediction model accuracy by 18% via feature engineering and hyperparameter tuning. Built MLOps pipelines for retraining, version control, and deployment using MLflow and GitHub Actions with robust regression testing. Automated ETL pipelines using Python and Airflow, saving 20+ hours weekly. Built RESTful APIs with Flask and Dockerized them for secure production deployment. Collaborated with data engineering to automate pipelines, reducing retraining time by 45%.

Machine Learning Engineer at Techimax

December 31, 2022 - July 23, 2025

Led recommendation system development using collaborative filtering, increasing user engagement by 25%. Implemented NLP pipelines for resume parsing and keyword extraction for HR tech clients, translating research prototypes into scalable models. Utilized MLflow for model tracking and version control, ensuring reproducibility and streamlined deployment with CI/CD. Optimized training and inference speeds on large datasets using GPU acceleration on AWS EC2 and containerized environments.

Generative AI Engineer | Founder's Team Member at Observo

June 1, 2025 - Present

Directed a 6-intern GenAI metrics squad, mentoring them in RAG pipelines and prompt engineering, which improved collaboration with product, ML, and DevOps teams. Engineered an automated evaluation engine that slashed model-release checkpoints by 50% and doubled deployment speed, leveraging Python and CI/CD practices for scalable ML integration. Reverse-engineered 45 rival metrics and distilled a core kit, establishing platform standards and supporting cohesive end-to-end deployment. Authored an LLM-as-Judge prompt suite and created a 50-case ground-truth dataset, boosting hallucination detection recall by 18 percentage points and integrating Grafana dashboards via GitHub Actions CI/CD for continuous monitoring.

Machine Learning Engineer at Cyrvana

July 1, 2024 - Present

Developed and deployed deep learning models for customer sentiment analysis using BERT and SpaCy, improving feedback classification accuracy by 32%. Created a real-time object detection system using YOLOv5 and OpenCV for retail automation, enhancing inventory management efficiency. Deployed scalable ML models using AWS SageMaker reducing prediction latency by 35% and improving inference reliability. Improved customer churn prediction accuracy by 18% via feature engineering and hyperparameter tuning. Built MLOps pipelines for retraining, version control, and deployment with MLflow and GitHub Actions. Automated ETL pipelines using Python and Airflow, saving 20+ hours weekly. Built RESTful APIs with Flask and Docker for production integration. Collaborated with data engineering to automate data pipelines reducing retraining time by 45% and managing compute resources efficiently.

Machine Learning Engineer at Techimax

December 31, 2022 - July 23, 2025

Led development of a recommendation system using collaborative filtering, increasing user engagement by 25%. Implemented NLP pipelines for resume parsing and keyword extraction for an HR tech client, translating prototypes into scalable models. Utilized MLflow for model tracking and versioning ensuring reproducibility and streamlined deployment with integrated CI/CD practices. Optimized training and inference speed on large datasets using GPU acceleration on AWS EC2, managing compute resources and containerized environments.

Generative AI Engineer | Founder's Team Member at Observo

June 1, 2025 - Present

Led a 6-intern team on generative AI metrics, mentoring in RAG pipelines and prompt engineering to improve collaboration across product, ML, and DevOps. Developed an automated evaluation engine that halved model-release checkpoints and doubled deployment speed using Python and CI/CD techniques. Reverse-engineered 45 competitor metrics to create a core set of 15 metrics establishing platform standards, using Python, LangChain, FAISS, and LLaMA-3 for deployment. Authored an LLM-as-Judge prompt suite and created a 50-case ground-truth dataset improving hallucination detection recall by 18%, integrating monitoring through Grafana dashboards and GitHub Actions CI/CD.

Machine Learning Engineer at Cyrvana

July 1, 2024 - Present

Developed and deployed deep learning models for customer sentiment analysis using BERT and SpaCy, improving classification accuracy by 32%. Built a real-time object detection system with YOLOv5 and OpenCV enhancing retail inventory management. Deployed scalable ML models on AWS SageMaker which reduced prediction latency by 35% and improved inference reliability adopting CI/CD best practices. Enhanced churn prediction accuracy by 18% through feature engineering and hyperparameter tuning. Created MLOps pipelines with MLflow and GitHub Actions for retraining, version control, and deployment, including regression testing. Automated ETL pipelines via Python and Airflow saving over 20 manual reporting hours weekly. Built RESTful APIs integrated with Docker for secure production deployment and collaborated on data pipelines reducing retraining time by 45%.

Machine Learning Engineer at Techimax

December 31, 2022 - August 26, 2025

Led development of a recommendation system using collaborative filtering increasing user engagement by 25%. Implemented NLP pipelines for resume parsing and keyword extraction for HR tech clients scaling research prototypes. Used MLflow for model tracking and reproducibility with integrated CI/CD processes. Optimized training and inference speed on large datasets leveraging GPU acceleration on AWS EC2, managing containerized environments and compute resources effectively.