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AI Engineer with 4+ years of experience building, deploying, and scaling production-grade ML/NLP and computer vision solutions across enterprise and client-facing environments. Strong expertise in Python, TensorFlow, PyTorch, Scikit-learn, Hugging Face, and OpenCV, with a focus on end-to-end delivery (training to inference). Proven track record of operationalizing AI using MLOps and cloud-native practices (MLflow, Docker, Kubernetes, CI/CD, REST deployments). Collaborates closely with data engineering and product teams to translate business problems into reliable, scalable AI systems aligned with US enterprise standards.…AI Engineer with 4+ years of experience building, deploying, and scaling production-grade ML/NLP and computer vision solutions across enterprise and client-facing environments. Strong expertise in Python, TensorFlow, PyTorch, Scikit-learn, Hugging Face, and OpenCV, with a focus on end-to-end delivery (training to inference). Proven track record of operationalizing AI using MLOps and cloud-native practices (MLflow, Docker, Kubernetes, CI/CD, REST deployments). Collaborates closely with data engineering and product teams to translate business problems into reliable, scalable AI systems aligned with US enterprise standards.

Pavan Sai Kumar Sambhangi

AI Engineer, Data Scientist, Programmer, +2

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AI Engineer with 4+ years of experience building, deploying, and scaling production-grade ML/NLP and computer vision solutions across enterprise and client-facing environments. Strong expertise in Python, TensorFlow, PyTorch, Scikit-learn, Hugging Face, and OpenCV, with a focus on end-to-end delivery (training to inference). Proven track record of operationalizing AI using MLOps and cloud-native practices (MLflow, Docker, Kubernetes, CI/CD, REST deployments). Collaborates closely with data engineering and product teams to translate business problems into reliable, scalable AI systems aligned with US enterprise standards.…AI Engineer with 4+ years of experience building, deploying, and scaling production-grade ML/NLP and computer vision solutions across enterprise and client-facing environments. Strong expertise in Python, TensorFlow, PyTorch, Scikit-learn, Hugging Face, and OpenCV, with a focus on end-to-end delivery (training to inference). Proven track record of operationalizing AI using MLOps and cloud-native practices (MLflow, Docker, Kubernetes, CI/CD, REST deployments). Collaborates closely with data engineering and product teams to translate business problems into reliable, scalable AI systems aligned with US enterprise standards.

Available to hire

AI Engineer with 4+ years of experience building, deploying, and scaling production-grade ML/NLP and computer vision solutions across enterprise and client-facing environments. Strong expertise in Python, TensorFlow, PyTorch, Scikit-learn, Hugging Face, and OpenCV, with a focus on end-to-end delivery (training to inference).

Proven track record of operationalizing AI using MLOps and cloud-native practices (MLflow, Docker, Kubernetes, CI/CD, REST deployments). Collaborates closely with data engineering and product teams to translate business problems into reliable, scalable AI systems aligned with US enterprise standards.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Work Experience

AI Engineer at ServiceNow

November 1, 2023 - Present

Designed and deployed end-to-end AI pipelines for enterprise products using Python, Scikit-learn, and TensorFlow for scalable training, inference, and lifecycle management across multiple platforms. Built production NLP models for text classification, NER, and sentiment analysis using BERT and Hugging Face Transformers, improving automated ticket routing accuracy by 28%. Developed deep learning architectures (CNNs and Transformer-based) for document intelligence and unstructured data processing to reduce manual operational effort. Implemented AI model deployment, monitoring, and versioning with MLflow, Docker, Kubernetes, and REST APIs, reducing model release cycles by 35% and improving production stability. Partnered with data engineering to design AI-ready ETL/feature pipelines using Spark, Kafka, and Airflow. Integrated CI/CD and A/B testing to increase production reliability and reduce post-deployment model issues by 22%.

AI Engineer at Infinite Infolab

April 1, 2020 - July 1, 2022

Implemented AI solutions using supervised and unsupervised learning for classification, regression, and clustering with Python, Scikit-learn, and XGBoost. Built feature engineering and feature selection pipelines to improve model robustness and generalization, delivering 25% performance improvements across client use cases. Developed NLP systems for text preprocessing, topic modeling, and sentiment analysis to generate automated insights from large unstructured datasets. Created computer vision pipelines using OpenCV, CNNs, and Faster R-CNN for image classification and object detection, reducing manual review workloads by 30%. Built scalable preprocessing and training pipelines using Pandas, Spark, and SQL. Deployed real-time inference services using Flask and FastAPI for integration with downstream applications. Collaborated with business and technical stakeholders to deliver deployable AI solutions without increasing infrastructure cost.