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Hi, I’m Sai Teja Reddy Kothakota, an AI/ML Engineer with 4 years of hands-on experience designing, building, and deploying scalable machine learning pipelines and cloud data platforms. I specialize in Python, PySpark, and deep learning frameworks, with a core focus on AWS and Snowflake. I excel in real-time and batch data integration, advanced transformations, and implementing robust MLOps architectures. I leverage Apache Airflow, Databricks, and Terraform to operationalize ML workflows, optimize cloud costs, and automate deployments. I’m adept at building end-to-end ML solutions, from data ingestion and feature engineering to model serving and monitoring. I have collaborated with data scientists to transition research prototypes into production-ready pipelines, and I’ve delivered cost-efficient, scalable systems that meet strict SLAs. I thrive in cross-functional teams and am passionate about delivering reliable, secure AI solutions that drive business outcomes.…Hi, I’m Sai Teja Reddy Kothakota, an AI/ML Engineer with 4 years of hands-on experience designing, building, and deploying scalable machine learning pipelines and cloud data platforms. I specialize in Python, PySpark, and deep learning frameworks, with a core focus on AWS and Snowflake. I excel in real-time and batch data integration, advanced transformations, and implementing robust MLOps architectures. I leverage Apache Airflow, Databricks, and Terraform to operationalize ML workflows, optimize cloud costs, and automate deployments. I’m adept at building end-to-end ML solutions, from data ingestion and feature engineering to model serving and monitoring. I have collaborated with data scientists to transition research prototypes into production-ready pipelines, and I’ve delivered cost-efficient, scalable systems that meet strict SLAs. I thrive in cross-functional teams and am passionate about delivering reliable, secure AI solutions that drive business outcomes.

Sai Teja Reddy Kothakota

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

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Hi, I’m Sai Teja Reddy Kothakota, an AI/ML Engineer with 4 years of hands-on experience designing, building, and deploying scalable machine learning pipelines and cloud data platforms. I specialize in Python, PySpark, and deep learning frameworks, with a core focus on AWS and Snowflake. I excel in real-time and batch data integration, advanced transformations, and implementing robust MLOps architectures. I leverage Apache Airflow, Databricks, and Terraform to operationalize ML workflows, optimize cloud costs, and automate deployments. I’m adept at building end-to-end ML solutions, from data ingestion and feature engineering to model serving and monitoring. I have collaborated with data scientists to transition research prototypes into production-ready pipelines, and I’ve delivered cost-efficient, scalable systems that meet strict SLAs. I thrive in cross-functional teams and am passionate about delivering reliable, secure AI solutions that drive business outcomes.…Hi, I’m Sai Teja Reddy Kothakota, an AI/ML Engineer with 4 years of hands-on experience designing, building, and deploying scalable machine learning pipelines and cloud data platforms. I specialize in Python, PySpark, and deep learning frameworks, with a core focus on AWS and Snowflake. I excel in real-time and batch data integration, advanced transformations, and implementing robust MLOps architectures. I leverage Apache Airflow, Databricks, and Terraform to operationalize ML workflows, optimize cloud costs, and automate deployments. I’m adept at building end-to-end ML solutions, from data ingestion and feature engineering to model serving and monitoring. I have collaborated with data scientists to transition research prototypes into production-ready pipelines, and I’ve delivered cost-efficient, scalable systems that meet strict SLAs. I thrive in cross-functional teams and am passionate about delivering reliable, secure AI solutions that drive business outcomes.

Available to hire

Hi, I’m Sai Teja Reddy Kothakota, an AI/ML Engineer with 4 years of hands-on experience designing, building, and deploying scalable machine learning pipelines and cloud data platforms. I specialize in Python, PySpark, and deep learning frameworks, with a core focus on AWS and Snowflake. I excel in real-time and batch data integration, advanced transformations, and implementing robust MLOps architectures. I leverage Apache Airflow, Databricks, and Terraform to operationalize ML workflows, optimize cloud costs, and automate deployments.
I’m adept at building end-to-end ML solutions, from data ingestion and feature engineering to model serving and monitoring. I have collaborated with data scientists to transition research prototypes into production-ready pipelines, and I’ve delivered cost-efficient, scalable systems that meet strict SLAs. I thrive in cross-functional teams and am passionate about delivering reliable, secure AI solutions that drive business outcomes.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Work Experience

AI/ML Engineer at Truist

August 1, 2024 - Present

Designed and implemented low-latency, real-time streaming pipelines using AWS Kinesis to ingest trading and pricing data for predictive models. Built robust real-time ML pipelines with Apache Airflow for DAG orchestration and Databricks (PySpark) for feature engineering, feeding Snowflake for model training. Containerized Python prediction APIs with Docker for portable deployments. Implemented Redis-based caching to accelerate real-time feature lookups. Tuned Spark jobs on Databricks for high-volume data, designed ELT pipelines in Snowflake using Snowpipe and Streams, and used MLflow to track experiments across 50+ fraud-detection models. Collaborated with data scientists to move research prototypes to production and optimized Snowflake performance and cost.

Software Engineer/ ML Engineer at Soft Sol

February 1, 2021 - July 31, 2023

Designed and deployed scalable predictive models for customer churn and risk scoring using Azure ML pipelines. Automated ETL + ML workflows in Azure Data Factory, integrating diverse data sources. Deployed ML models as REST APIs with Flask and Azure Functions, enabling real-time inference. Implemented automated monitoring and drift detection, and built PySpark feature pipelines for telemetry data. Included data validation to improve training data quality.