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Hi, I am Sandeep Athota, an AI/ML Engineer with 3 years of hands-on experience designing, developing, and deploying scalable ML models and AI solutions. I am proficient in Python, linear and logistic regression, CNNs, Generative AI, and NLP, with hands-on experience building and fine-tuning LLMs and AI agents. I excel at orchestrating data workflows with Apache Airflow, building robust visualizations with Matplotlib, and delivering end-to-end ML pipelines using Scikit-learn and TensorFlow. I am passionate about applying AI to real-world problems across research and production, and I enjoy collaborating with cross-functional teams to deploy reliable, high-performance AI solutions.…Hi, I am Sandeep Athota, an AI/ML Engineer with 3 years of hands-on experience designing, developing, and deploying scalable ML models and AI solutions. I am proficient in Python, linear and logistic regression, CNNs, Generative AI, and NLP, with hands-on experience building and fine-tuning LLMs and AI agents. I excel at orchestrating data workflows with Apache Airflow, building robust visualizations with Matplotlib, and delivering end-to-end ML pipelines using Scikit-learn and TensorFlow. I am passionate about applying AI to real-world problems across research and production, and I enjoy collaborating with cross-functional teams to deploy reliable, high-performance AI solutions.

Sandeep Athota

AI Engineer, Data Scientist, Full Stack Developer, +6

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Hi, I am Sandeep Athota, an AI/ML Engineer with 3 years of hands-on experience designing, developing, and deploying scalable ML models and AI solutions. I am proficient in Python, linear and logistic regression, CNNs, Generative AI, and NLP, with hands-on experience building and fine-tuning LLMs and AI agents. I excel at orchestrating data workflows with Apache Airflow, building robust visualizations with Matplotlib, and delivering end-to-end ML pipelines using Scikit-learn and TensorFlow. I am passionate about applying AI to real-world problems across research and production, and I enjoy collaborating with cross-functional teams to deploy reliable, high-performance AI solutions.…Hi, I am Sandeep Athota, an AI/ML Engineer with 3 years of hands-on experience designing, developing, and deploying scalable ML models and AI solutions. I am proficient in Python, linear and logistic regression, CNNs, Generative AI, and NLP, with hands-on experience building and fine-tuning LLMs and AI agents. I excel at orchestrating data workflows with Apache Airflow, building robust visualizations with Matplotlib, and delivering end-to-end ML pipelines using Scikit-learn and TensorFlow. I am passionate about applying AI to real-world problems across research and production, and I enjoy collaborating with cross-functional teams to deploy reliable, high-performance AI solutions.

Available to hire

Hi, I am Sandeep Athota, an AI/ML Engineer with 3 years of hands-on experience designing, developing, and deploying scalable ML models and AI solutions. I am proficient in Python, linear and logistic regression, CNNs, Generative AI, and NLP, with hands-on experience building and fine-tuning LLMs and AI agents.

I excel at orchestrating data workflows with Apache Airflow, building robust visualizations with Matplotlib, and delivering end-to-end ML pipelines using Scikit-learn and TensorFlow. I am passionate about applying AI to real-world problems across research and production, and I enjoy collaborating with cross-functional teams to deploy reliable, high-performance AI solutions.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Language

English

Fluent

Work Experience

AI/ML Engineer at JP Morgan Chase & CO.

January 1, 2025 - Present

Engineered and deployed a large-scale, multi-modal AI pipeline to predict customer financial risk and optimize client management strategies across Chase's retail branches. Integrated data from 950,000+ client records and 1.4 million document images to support proactive portfolio oversight. Built a hybrid system combining CNNs with attention for information extraction and anomaly detection, and modeled sequential client behavior with LSTMs in PyTorch using 12+ months of historical data. Developed a scalable feature engineering workflow in Snowflake, creating a unified 360-degree client view and reducing feature prep time by 60%. Implemented a robust ensemble and established continuous MLOps automation for retraining/validation, cutting drift and deployment cycles. Used a pre-trained LLM to augment data labeling for rare-edge cases, increasing minority-class data and improving fairness. Automated real-time KPI dashboards in Power BI for multiple business units, saving manual reporting ef

Machine Learning Engineer at Accenture

September 1, 2021 - December 1, 2023

Architected and implemented a full-scale MLOps framework on GCP for a predictive maintenance solution, orchestrating the entire lifecycle of multiple models and reducing retraining cycles by 70%. Designed a high-throughput multi-model microservice using FastAPI, Docker, and GKE, hosting a fine-tuned BERT classifier and a spaCy NER model, serving 50,000+ daily requests and scaling to handle 50% surge with zero downtime. Integrated Kubeflow for pipelines and MLflow for centralized experiment tracking and model registry, consolidating 150+ model versions. Automated retraining triggered by data drift (<5%) maintaining accuracy above 94% F1, reducing manual oversight by 40 hours/month. The solution contributed to a 15% reduction in unplanned downtime and ~$2.5M in annual savings.