Hi, I’m Deepak Kumar, an AI/ML engineer with around four years of hands-on experience designing and deploying scalable machine learning systems. I’ve built end-to-end ML pipelines, advanced generative AI capabilities, and data engineering solutions across cybersecurity, healthcare, and enterprise environments. I enjoy turning complex technical problems into measurable business impact and collaborating with cross-functional teams to drive real-world outcomes. I specialize in end-to-end ML pipelines using Python, TensorFlow, XGBoost, and Spark, with hands-on expertise in unsupervised anomaly detection, time-series forecasting, and model explainability. I’ve worked on RAG-based systems, fine-tuning LLMs with LoRA, and integrating vector databases. I’ve deployed low-latency inference services on Kubernetes and cloud platforms, and I’m proficient in monitoring, drift detection, and production-grade ML ops practices. I’m passionate about translating technical challenges into tangible improvements in operational efficiency and decision-making through AI-driven solutions.

Deepak Kumar Tummala

Hi, I’m Deepak Kumar, an AI/ML engineer with around four years of hands-on experience designing and deploying scalable machine learning systems. I’ve built end-to-end ML pipelines, advanced generative AI capabilities, and data engineering solutions across cybersecurity, healthcare, and enterprise environments. I enjoy turning complex technical problems into measurable business impact and collaborating with cross-functional teams to drive real-world outcomes. I specialize in end-to-end ML pipelines using Python, TensorFlow, XGBoost, and Spark, with hands-on expertise in unsupervised anomaly detection, time-series forecasting, and model explainability. I’ve worked on RAG-based systems, fine-tuning LLMs with LoRA, and integrating vector databases. I’ve deployed low-latency inference services on Kubernetes and cloud platforms, and I’m proficient in monitoring, drift detection, and production-grade ML ops practices. I’m passionate about translating technical challenges into tangible improvements in operational efficiency and decision-making through AI-driven solutions.

Available to hire

Hi, I’m Deepak Kumar, an AI/ML engineer with around four years of hands-on experience designing and deploying scalable machine learning systems. I’ve built end-to-end ML pipelines, advanced generative AI capabilities, and data engineering solutions across cybersecurity, healthcare, and enterprise environments. I enjoy turning complex technical problems into measurable business impact and collaborating with cross-functional teams to drive real-world outcomes.

I specialize in end-to-end ML pipelines using Python, TensorFlow, XGBoost, and Spark, with hands-on expertise in unsupervised anomaly detection, time-series forecasting, and model explainability. I’ve worked on RAG-based systems, fine-tuning LLMs with LoRA, and integrating vector databases. I’ve deployed low-latency inference services on Kubernetes and cloud platforms, and I’m proficient in monitoring, drift detection, and production-grade ML ops practices. I’m passionate about translating technical challenges into tangible improvements in operational efficiency and decision-making through AI-driven solutions.

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Experience Level

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

English
Fluent

Work Experience

AI/ML Engineer at Cisco
June 1, 2024 - Present
Built unsupervised anomaly detection models using TensorFlow and Autoencoders to uncover zero-day network threats within Hypershield security modules, cutting false positive alerts by 18%.
Associate Data Scientist at AbbVie
June 1, 2023 - March 1, 2024
Engineered unsupervised anomaly detection models using TensorFlow and Autoencoders to identify zero-day network threats within HyperShield security modules, reducing false positive alerts by 18%.
Data Engineer at Magna Infotech
September 1, 2020 - December 1, 2021
Assisted in building and maintaining ETL pipelines using Python and SQL to extract, transform, and load data from multiple sources, ensuring accurate and consistent datasets for analytics teams. Supported design and optimization of database tables in MySQL and PostgreSQL.

Education

Master's in Information and Technology Management at Lindsey Wilson University
January 11, 2030 - April 1, 2024
at Sathyabama University
June 1, 2021 - March 27, 2026
Master's in Information and Technology Management at Lindsey Wilson University
January 11, 2030 - April 1, 2024
Bachelor of Technology in Computer Science Engineering at Sathyabama University
January 11, 2030 - June 1, 2021
Master's in Information and Technology Management at Lindsey Wilson University
January 11, 2030 - April 1, 2024
Bachelor's Degree at Sathyabama University
January 11, 2030 - June 1, 2021

Qualifications

Add your qualifications or awards here.

Industry Experience

Healthcare, Life Sciences, Software & Internet, Professional Services, Media & Entertainment