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I am a Machine Learning Engineer with 4+ years of experience in IoT, edge AI, and enterprise ML deployments. I design, train, and deploy ML and deep learning models for computer vision, time-series forecasting, anomaly detection, and predictive analytics, with hands-on experience in embedded systems development on Embedded Linux platforms using Python and C++. I have built edge-optimized ML pipelines and led MLOps workflows, including OTA updates, to deliver scalable solutions. I excel at integrating IoT devices with cloud platforms like AWS and Azure, building robust data pipelines, and fine-tuning large language models for practical business applications. I enjoy collaborating with cross-functional teams to apply generative AI and edge intelligence, enabling intelligent, low-latency IoT ecosystems and real-time analytics for automation and operational improvements.…I am a Machine Learning Engineer with 4+ years of experience in IoT, edge AI, and enterprise ML deployments. I design, train, and deploy ML and deep learning models for computer vision, time-series forecasting, anomaly detection, and predictive analytics, with hands-on experience in embedded systems development on Embedded Linux platforms using Python and C++. I have built edge-optimized ML pipelines and led MLOps workflows, including OTA updates, to deliver scalable solutions. I excel at integrating IoT devices with cloud platforms like AWS and Azure, building robust data pipelines, and fine-tuning large language models for practical business applications. I enjoy collaborating with cross-functional teams to apply generative AI and edge intelligence, enabling intelligent, low-latency IoT ecosystems and real-time analytics for automation and operational improvements.

Ponugoti Sushma

Data Scientist, AI Engineer, Developer, +3

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I am a Machine Learning Engineer with 4+ years of experience in IoT, edge AI, and enterprise ML deployments. I design, train, and deploy ML and deep learning models for computer vision, time-series forecasting, anomaly detection, and predictive analytics, with hands-on experience in embedded systems development on Embedded Linux platforms using Python and C++. I have built edge-optimized ML pipelines and led MLOps workflows, including OTA updates, to deliver scalable solutions. I excel at integrating IoT devices with cloud platforms like AWS and Azure, building robust data pipelines, and fine-tuning large language models for practical business applications. I enjoy collaborating with cross-functional teams to apply generative AI and edge intelligence, enabling intelligent, low-latency IoT ecosystems and real-time analytics for automation and operational improvements.…I am a Machine Learning Engineer with 4+ years of experience in IoT, edge AI, and enterprise ML deployments. I design, train, and deploy ML and deep learning models for computer vision, time-series forecasting, anomaly detection, and predictive analytics, with hands-on experience in embedded systems development on Embedded Linux platforms using Python and C++. I have built edge-optimized ML pipelines and led MLOps workflows, including OTA updates, to deliver scalable solutions. I excel at integrating IoT devices with cloud platforms like AWS and Azure, building robust data pipelines, and fine-tuning large language models for practical business applications. I enjoy collaborating with cross-functional teams to apply generative AI and edge intelligence, enabling intelligent, low-latency IoT ecosystems and real-time analytics for automation and operational improvements.

Available to hire

I am a Machine Learning Engineer with 4+ years of experience in IoT, edge AI, and enterprise ML deployments. I design, train, and deploy ML and deep learning models for computer vision, time-series forecasting, anomaly detection, and predictive analytics, with hands-on experience in embedded systems development on Embedded Linux platforms using Python and C++. I have built edge-optimized ML pipelines and led MLOps workflows, including OTA updates, to deliver scalable solutions.

I excel at integrating IoT devices with cloud platforms like AWS and Azure, building robust data pipelines, and fine-tuning large language models for practical business applications. I enjoy collaborating with cross-functional teams to apply generative AI and edge intelligence, enabling intelligent, low-latency IoT ecosystems and real-time analytics for automation and operational improvements.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

English

Fluent

Work Experience

ML Engineer at Allstate

February 1, 2025 - Present

Designed, expanded, and deployed production-grade ML models for fraud detection, risk modeling, and telematics analytics in a high-volume enterprise setting. Built scalable, low-latency inference pipelines and integrated LLMs for automated customer support, claims data summarization, and personalized marketing content, improving response accuracy and reducing manual workload. Collaborated with data engineers to develop end-to-end data pipelines—ingestion, cleaning, feature engineering, and model training—to ensure a clean path from raw data to ML-ready datasets for continuous improvement. Applied supervised, unsupervised, and reinforcement learning techniques, selecting algorithms aligned with business objectives to maximize predictive accuracy. Established MLOps pipelines using MLflow, Kubeflow, and SageMaker, automating training, evaluation, deployment, and monitoring, while ensuring reproducibility and version control. Managed model governance, including version tracking, artifa

ML Engineer at Adons SoftTech

August 1, 2020 - July 1, 2023

Developed, trained, and fine-tuned ML and deep learning models for regression, classification, clustering, and predictive analytics tasks. Partnered with data engineers to design end-to-end data pipelines, improving data processing efficiency by 20%. Deployed models to AWS production environments, monitored performance, and implemented optimizations to reduce latency and improve reliability. Wrote clean, modular Python code using scikit-learn, pandas, NumPy, TensorFlow, and PyTorch, following software engineering best practices. Conducted exploratory data analysis (EDA) and feature engineering to boost predictive accuracy by 15%. Collaborated with cross-functional teams to integrate ML models into applications and deliver actionable insights to clients. Participated in code reviews and knowledge-sharing sessions to promote ML engineering best practices. Researched and prototyped innovative ML solutions to address real-world enterprise needs.

IoT & ML Developer at CitiusTech

December 1, 2018 - June 1, 2019

Assisted in designing and implementing IoT solutions by integrating over 15 sensors and embedded devices, enabling real-time data collection and improving system monitoring efficiency by 20%. Supported cloud data pipelines on Azure, handling large IoT datasets for storage and processing, and improving data pipeline efficiency by 25%. Implemented secure communication between devices and gateways using Python and C++ via MQTT and HTTP, reducing data latency by 15%. Built ML models for predictive analytics and anomaly detection using scikit-learn and TensorFlow, achieving 18% accuracy improvement in test scenarios. Helped integrate IoT data streams with cloud dashboards and analytics platforms, and reduced data synchronization time by 20%. Gained hands-on experience in end-to-end IoT and ML pipelines, including data collection, cloud integration, and model deployment.