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I am an innovative and results-driven Senior Machine Learning Engineer with 8+ years of multi-industry experience, specializing in GenAI, LLMs, MLOps, NLP, and end-to-end ML system design. I excel at architecting scalable ML infrastructure and LLM-driven solutions, with a proven track record of optimizing large-scale training and inference workflows for enterprise-grade AI applications. I enjoy collaborating with cross-functional teams to translate complex problems into practical, impactful AI solutions. I have hands-on experience with foundation model fine-tuning, retrieval-augmented generation (RAG), and production-grade deployment across cloud platforms. I am adept at building robust ML pipelines, implementing MLOps, and delivering explainable AI that clinicians and business users can trust. My approach blends research rigor with scalable engineering to drive measurable business value and responsible AI adoption.…I am an innovative and results-driven Senior Machine Learning Engineer with 8+ years of multi-industry experience, specializing in GenAI, LLMs, MLOps, NLP, and end-to-end ML system design. I excel at architecting scalable ML infrastructure and LLM-driven solutions, with a proven track record of optimizing large-scale training and inference workflows for enterprise-grade AI applications. I enjoy collaborating with cross-functional teams to translate complex problems into practical, impactful AI solutions. I have hands-on experience with foundation model fine-tuning, retrieval-augmented generation (RAG), and production-grade deployment across cloud platforms. I am adept at building robust ML pipelines, implementing MLOps, and delivering explainable AI that clinicians and business users can trust. My approach blends research rigor with scalable engineering to drive measurable business value and responsible AI adoption.

Nithin Reddy Gantla

Data Scientist, AI Engineer, Data Analyst, +2

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I am an innovative and results-driven Senior Machine Learning Engineer with 8+ years of multi-industry experience, specializing in GenAI, LLMs, MLOps, NLP, and end-to-end ML system design. I excel at architecting scalable ML infrastructure and LLM-driven solutions, with a proven track record of optimizing large-scale training and inference workflows for enterprise-grade AI applications. I enjoy collaborating with cross-functional teams to translate complex problems into practical, impactful AI solutions. I have hands-on experience with foundation model fine-tuning, retrieval-augmented generation (RAG), and production-grade deployment across cloud platforms. I am adept at building robust ML pipelines, implementing MLOps, and delivering explainable AI that clinicians and business users can trust. My approach blends research rigor with scalable engineering to drive measurable business value and responsible AI adoption.…I am an innovative and results-driven Senior Machine Learning Engineer with 8+ years of multi-industry experience, specializing in GenAI, LLMs, MLOps, NLP, and end-to-end ML system design. I excel at architecting scalable ML infrastructure and LLM-driven solutions, with a proven track record of optimizing large-scale training and inference workflows for enterprise-grade AI applications. I enjoy collaborating with cross-functional teams to translate complex problems into practical, impactful AI solutions. I have hands-on experience with foundation model fine-tuning, retrieval-augmented generation (RAG), and production-grade deployment across cloud platforms. I am adept at building robust ML pipelines, implementing MLOps, and delivering explainable AI that clinicians and business users can trust. My approach blends research rigor with scalable engineering to drive measurable business value and responsible AI adoption.

Available to hire

I am an innovative and results-driven Senior Machine Learning Engineer with 8+ years of multi-industry experience, specializing in GenAI, LLMs, MLOps, NLP, and end-to-end ML system design. I excel at architecting scalable ML infrastructure and LLM-driven solutions, with a proven track record of optimizing large-scale training and inference workflows for enterprise-grade AI applications. I enjoy collaborating with cross-functional teams to translate complex problems into practical, impactful AI solutions.

I have hands-on experience with foundation model fine-tuning, retrieval-augmented generation (RAG), and production-grade deployment across cloud platforms. I am adept at building robust ML pipelines, implementing MLOps, and delivering explainable AI that clinicians and business users can trust. My approach blends research rigor with scalable engineering to drive measurable business value and responsible AI adoption.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

English

Fluent

Work Experience

Senior Data Scientist / ML Engineer at LUMERIS

January 1, 2024 - November 18, 2025

Designed and implemented predictive healthcare analytics models using Python and PyTorch to optimize patient risk stratification. Built NLP pipelines for clinical text classification using Hugging Face Transformers and SpaCy, automating document analysis. Engineered end-to-end data ingestion workflows on Google Cloud Composer and Apache Kafka to handle large-scale medical records. Developed scalable MLOps frameworks with MLflow and Vertex AI to monitor, retrain, and deploy healthcare models. Integrated structured and unstructured data via Google Bigtable and Cloud Storage for longitudinal analysis. Led distributed data processing on Google Dataproc for high-volume claims analytics. Built explainable AI solutions with SHAP and LIME and created fraud detection frameworks using anomaly detection in PyTorch. These efforts reduced processing time, improved prediction accuracy, and supported compliant, interpretable AI in healthcare.

Data Scientist at Westfield Insurance

December 31, 2023 - December 31, 2023

Developed financial risk assessment models in Python and PyTorch to optimize underwriting decisions. Built churn prediction frameworks using Azure ML and scikit-learn to reduce policyholder attrition. Automated claims workflows with Azure Databricks, Azure ML, and Python. Built large-scale data pipelines using Azure Data Factory and Event Hubs for real-time processing. Applied NLP using Azure Cognitive Services and SpaCy to analyze contracts and claims documents. Designed forecasting models with Statsmodels. Created explainable SHAP and LIME AI models integrated with Azure Synapse for transparent underwriting decisions. Automated fraud investigations using Docker, Kubernetes, and Azure Functions. Implemented MLOps with MLflow and Azure ML and integrated external datasets with Cosmos DB and Synapse. Developed neural network–based forecasting models using TensorFlow and PyTorch.

Senior ML Engineer at Northern Trust Bank

May 31, 2022 - May 31, 2022

Developed GPT-based LLM pipelines for enterprise NLP, including document summarization, insights extraction, and contextual query processing. Orchestrated end-to-end GPT/LLM training and deployment workflows with Apache Airflow and Argo Workflows. Implemented model versioning and experiment tracking using MLflow and DVC. Containerized LLM inference pipelines with Docker and deployed on Kubernetes using Helm. Deployed production-grade endpoints with TensorFlow Serving, TorchServe, and Triton Inference Server. Built feature preprocessing pipelines to transform structured and unstructured data into embeddings and tokenized inputs. Integrated SHAP/LIME explainability to support compliance and risk management. Automated CI/CD workflows with GitHub Actions and Terraform. Optimized GPU/CPU resource allocation for enterprise workloads. Collaborated on evaluation metrics and benchmarking for domain-specific LLM outputs.

Data Scientist/ ML Engineer at Quantiphi

January 31, 2020 - January 31, 2020

Fine-tuned transformer models for intent classification, contextual sentence embedding, and multilingual named entity recognition using PyTorch and Hugging Face Transformers. Automated experiment lifecycle with MLflow, Airflow, and Git. Implemented explainability workflows with SHAP, LIME, and Integrated Gradients. Preprocessed unstructured corpora using SpaCy, regex, and TF-IDF to generate feature matrices for downstream classification and similarity modeling. Built analytical datasets from SQL, PySpark, and Pandas, and integrated dashboards for stakeholders. Implemented end-to-end experimentation and model tracking.

Associate Data Scientist/ ML Engineer at SigTuple

November 30, 2018 - November 30, 2018

Trained classification models using scikit-learn and XGBoost with feature engineering and class rebalancing. Built statistical tests with statsmodels to detect variance shifts in diagnostic results. Engineered structured features from unformatted logs using PySpark on Hadoop, storing outputs on AWS S3. Designed Tableau dashboards to surface misclassification patterns and low-confidence predictions. Versioned feature sets and experiments with Git, and tuned XGBoost hyperparameters to mitigate overfitting on noisy clinical data.

Data Analyst at Nielsen

January 31, 2017 - January 31, 2017

Queried multi-source sales data using SQL across Oracle and SQL Server to generate brand performance metrics for CPG analytics. Automated QA checks with Python (Pandas) to validate joins and detect drift. Created Tableau dashboards visualizing channel-wise sales trends, price bands, and volume growth.