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AI/ML Engineer with 5+ years of experience building machine learning, NLP, and Generative AI solutions across cloud environments. Experienced in developing scalable ML pipelines, deploying production models using AWS, Snowflake, Airflow, Docker, Kubernetes, and MLflow, and implementing RAG-based applications using LangChain and vector databases. Proven track record of delivering predictive analytics, automation, and AI-driven business solutions generating measurable revenue growth and operational efficiency.…AI/ML Engineer with 5+ years of experience building machine learning, NLP, and Generative AI solutions across cloud environments. Experienced in developing scalable ML pipelines, deploying production models using AWS, Snowflake, Airflow, Docker, Kubernetes, and MLflow, and implementing RAG-based applications using LangChain and vector databases. Proven track record of delivering predictive analytics, automation, and AI-driven business solutions generating measurable revenue growth and operational efficiency.

Sampreethi Bokka

AI Engineer, Data Scientist, Web Developer, +1

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AI/ML Engineer with 5+ years of experience building machine learning, NLP, and Generative AI solutions across cloud environments. Experienced in developing scalable ML pipelines, deploying production models using AWS, Snowflake, Airflow, Docker, Kubernetes, and MLflow, and implementing RAG-based applications using LangChain and vector databases. Proven track record of delivering predictive analytics, automation, and AI-driven business solutions generating measurable revenue growth and operational efficiency.…AI/ML Engineer with 5+ years of experience building machine learning, NLP, and Generative AI solutions across cloud environments. Experienced in developing scalable ML pipelines, deploying production models using AWS, Snowflake, Airflow, Docker, Kubernetes, and MLflow, and implementing RAG-based applications using LangChain and vector databases. Proven track record of delivering predictive analytics, automation, and AI-driven business solutions generating measurable revenue growth and operational efficiency.

Available to hire

AI/ML Engineer with 5+ years of experience building machine learning, NLP, and Generative AI solutions across cloud environments. Experienced in developing scalable ML pipelines, deploying production models using AWS, Snowflake, Airflow, Docker, Kubernetes, and MLflow, and implementing RAG-based applications using LangChain and vector databases.

Proven track record of delivering predictive analytics, automation, and AI-driven business solutions generating measurable revenue growth and operational efficiency.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Work Experience

AI/ML Engineer at Gartner, USA

January 1, 2025 - Present

Orchestrated scalable machine learning pipelines using Airflow, Snowflake, and Python, reducing processing latency by 12%. Spearheaded predictive forecasting solutions using TensorFlow and feature engineering. Built RAG-based enterprise search applications using LangChain, OpenAI embeddings, Pinecone, and semantic retrieval pipelines, improving knowledge discovery accuracy by 25%. Streamlined production deployment workflows through Docker, Kubernetes, and MLflow for governance and traceability. Implemented model drift monitoring mechanisms and delivered automated data products integrating APIs and PostgreSQL, saving $300K annually. Built recommendation algorithms to increase engagement by 14% and supported experimentation frameworks for A/B testing. Delivered predictive risk intelligence solutions contributing to approximately $1M in incremental revenue opportunities.

Software Engineer at Hexaware Technology, India

January 1, 2020 - July 1, 2023

Crafted ETL workflows integrating customer, operational, and transactional datasets across enterprise systems. Automated recurring reporting using SQL, Power BI, and Python, improving efficiency by 17%. Administered large-scale data transformation processes using Spark and distributed computing. Developed statistical models for demand forecasting, inventory planning, and resource allocation. Implemented data quality controls reducing discrepancies by 12%. Consolidated multi-source datasets via API integrations for unified analytics. Supported cloud migration initiatives on AWS-based platforms, improved classification algorithms for customer targeting (9% stronger campaign performance), and modernized dashboards to enable KPI transparency with revenue growth exceeding $500K. Optimized database queries to reduce execution times by 15%.