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Hi, I’m Sandeep Athota, an AI/ML engineer focused on turning research into robust production systems on Google Cloud Platform. I enjoy building scalable, cloud-native ML pipelines and collaborating across teams to deliver measurable business value. I thrive in fast-paced environments and am passionate about automating the end-to-end ML lifecycle to drive real impact in production. I specialize in deploying low-latency, high-availability ML services, implementing MLOps best practices, and continuously improving model performance and reliability in production. I’m driven by solving complex problems at the intersection of data, engineering, and business strategy, and I love transforming prototypes into production-ready solutions that scale.…Hi, I’m Sandeep Athota, an AI/ML engineer focused on turning research into robust production systems on Google Cloud Platform. I enjoy building scalable, cloud-native ML pipelines and collaborating across teams to deliver measurable business value. I thrive in fast-paced environments and am passionate about automating the end-to-end ML lifecycle to drive real impact in production. I specialize in deploying low-latency, high-availability ML services, implementing MLOps best practices, and continuously improving model performance and reliability in production. I’m driven by solving complex problems at the intersection of data, engineering, and business strategy, and I love transforming prototypes into production-ready solutions that scale.

Sandeep Athota

AI Engineer, Data Scientist, Full Stack Developer, +2

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Hi, I’m Sandeep Athota, an AI/ML engineer focused on turning research into robust production systems on Google Cloud Platform. I enjoy building scalable, cloud-native ML pipelines and collaborating across teams to deliver measurable business value. I thrive in fast-paced environments and am passionate about automating the end-to-end ML lifecycle to drive real impact in production. I specialize in deploying low-latency, high-availability ML services, implementing MLOps best practices, and continuously improving model performance and reliability in production. I’m driven by solving complex problems at the intersection of data, engineering, and business strategy, and I love transforming prototypes into production-ready solutions that scale.…Hi, I’m Sandeep Athota, an AI/ML engineer focused on turning research into robust production systems on Google Cloud Platform. I enjoy building scalable, cloud-native ML pipelines and collaborating across teams to deliver measurable business value. I thrive in fast-paced environments and am passionate about automating the end-to-end ML lifecycle to drive real impact in production. I specialize in deploying low-latency, high-availability ML services, implementing MLOps best practices, and continuously improving model performance and reliability in production. I’m driven by solving complex problems at the intersection of data, engineering, and business strategy, and I love transforming prototypes into production-ready solutions that scale.

Available to hire

Hi, I’m Sandeep Athota, an AI/ML engineer focused on turning research into robust production systems on Google Cloud Platform. I enjoy building scalable, cloud-native ML pipelines and collaborating across teams to deliver measurable business value. I thrive in fast-paced environments and am passionate about automating the end-to-end ML lifecycle to drive real impact in production.

I specialize in deploying low-latency, high-availability ML services, implementing MLOps best practices, and continuously improving model performance and reliability in production. I’m driven by solving complex problems at the intersection of data, engineering, and business strategy, and I love transforming prototypes into production-ready solutions that scale.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

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.