I’m Udaykiran Vemala, an AI/ML engineer with 3+ years of experience designing, developing, and deploying scalable machine learning solutions across cloud and enterprise environments. I build predictive models, NLP pipelines, and Generative AI applications using Python, TensorFlow, PyTorch, and cloud platforms like AWS, Azure, and Databricks. I champion production-grade AI systems, optimize model performance, automate ML pipelines, and deliver data-driven business solutions that improve operational efficiency and deployment scalability.\n\nI specialize in deep learning, LLMs, computer vision, cloud-native AI architecture, and end-to-end ML lifecycle management within Agile development environments. I enjoy collaborating with cross-functional teams to turn data into actionable insights and measurable business impact.

Udaykiran Vemala

I’m Udaykiran Vemala, an AI/ML engineer with 3+ years of experience designing, developing, and deploying scalable machine learning solutions across cloud and enterprise environments. I build predictive models, NLP pipelines, and Generative AI applications using Python, TensorFlow, PyTorch, and cloud platforms like AWS, Azure, and Databricks. I champion production-grade AI systems, optimize model performance, automate ML pipelines, and deliver data-driven business solutions that improve operational efficiency and deployment scalability.\n\nI specialize in deep learning, LLMs, computer vision, cloud-native AI architecture, and end-to-end ML lifecycle management within Agile development environments. I enjoy collaborating with cross-functional teams to turn data into actionable insights and measurable business impact.

Available to hire

I’m Udaykiran Vemala, an AI/ML engineer with 3+ years of experience designing, developing, and deploying scalable machine learning solutions across cloud and enterprise environments. I build predictive models, NLP pipelines, and Generative AI applications using Python, TensorFlow, PyTorch, and cloud platforms like AWS, Azure, and Databricks. I champion production-grade AI systems, optimize model performance, automate ML pipelines, and deliver data-driven business solutions that improve operational efficiency and deployment scalability.\n\nI specialize in deep learning, LLMs, computer vision, cloud-native AI architecture, and end-to-end ML lifecycle management within Agile development environments. I enjoy collaborating with cross-functional teams to turn data into actionable insights and measurable business impact.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
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Language

English
Fluent

Work Experience

AI/ML Engineer Intern at Hugging Face
November 1, 2025 - Present
Assisted in developing NLP pipelines using Hugging Face Transformers and Python for text classification and summarization tasks, improving model inference efficiency by 18% during internal testing. Supported fine-tuning of BERT and RoBERTa models on domain-specific datasets, improving accuracy and validation performance across experimentation workflows. Collaborated with research and engineering teams to evaluate LLM performance metrics, prompt responses, and dataset quality using PyTorch, Pandas, and Jupyter Notebook environments. Built lightweight FastAPI endpoints for ML model inference testing and integrated AI models into internal prototype applications for NLP-based automation use cases. Assisted with preprocessing and cleaning structured and unstructured datasets, reducing data inconsistencies and improving training dataset readiness for ML experiments. Participated in model monitoring, documentation, and experiment tracking activities using MLflow and Git.
AI/ML Engineer at Cognizant
July 1, 2021 - December 1, 2023
Designed and implemented machine learning solutions using Python, Scikit-learn, TensorFlow, and SQL to support enterprise analytics and automation initiatives, improving operational efficiency by 40% and reducing manual processing across business workflows. Developed predictive analytics and recommendation models, improving forecasting accuracy and customer engagement metrics by 26%. Built scalable ETL and big data processing pipelines using Apache Spark, PySpark, Kafka, and Airflow to process structured and unstructured datasets exceeding 20TB, improving data ingestion performance by 45% and ensuring real-time analytics availability. Implemented deep learning and computer vision models using TensorFlow, Keras, and OpenCV for image recognition and anomaly detection use cases, improving defect detection accuracy by 33% while minimizing false-negative rates in production systems. Developed NLP-based text analytics and sentiment analysis solutions using SpaCy, NLTK, and Hugging Face model

Education

Master of Data Science at Rowan University, Glassboro, NJ, USA
January 1, 2024 - December 31, 2025
Bachelor of Computer Science at Gitam University, Vizag, AP, India
July 1, 2019 - April 1, 2023

Qualifications

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Industry Experience

Software & Internet, Professional Services