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AI/ML Engineer with 4 years of experience designing GenAI-enabled analytical frameworks and applied machine learning for regulated financial services. Builds data models and transformation pipelines in Python, SQL, PySpark, and Databricks, and leads prompt engineering and LLM fine-tuning with LangChain, LlamaIndex, and Hugging Face Transformers against accuracy, compliance, and ethical AI standards. Strong predictive modeling and experimentation record, including a 0.89 AUC-ROC credit risk model and a 22% reduction in false-positive compliance alerts at 95% recall. Translates model results and behavioral insights into executive storytelling through Power BI and Tableau across a $2B+ managed asset portfolio, aiming to bring production GenAI engineering and business-facing analytics to enterprise decision intelligence and AI product strategy.…AI/ML Engineer with 4 years of experience designing GenAI-enabled analytical frameworks and applied machine learning for regulated financial services. Builds data models and transformation pipelines in Python, SQL, PySpark, and Databricks, and leads prompt engineering and LLM fine-tuning with LangChain, LlamaIndex, and Hugging Face Transformers against accuracy, compliance, and ethical AI standards. Strong predictive modeling and experimentation record, including a 0.89 AUC-ROC credit risk model and a 22% reduction in false-positive compliance alerts at 95% recall. Translates model results and behavioral insights into executive storytelling through Power BI and Tableau across a $2B+ managed asset portfolio, aiming to bring production GenAI engineering and business-facing analytics to enterprise decision intelligence and AI product strategy.

Arshita R

AI Engineer, Data Scientist, Programmer, +3

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AI/ML Engineer with 4 years of experience designing GenAI-enabled analytical frameworks and applied machine learning for regulated financial services. Builds data models and transformation pipelines in Python, SQL, PySpark, and Databricks, and leads prompt engineering and LLM fine-tuning with LangChain, LlamaIndex, and Hugging Face Transformers against accuracy, compliance, and ethical AI standards. Strong predictive modeling and experimentation record, including a 0.89 AUC-ROC credit risk model and a 22% reduction in false-positive compliance alerts at 95% recall. Translates model results and behavioral insights into executive storytelling through Power BI and Tableau across a $2B+ managed asset portfolio, aiming to bring production GenAI engineering and business-facing analytics to enterprise decision intelligence and AI product strategy.…AI/ML Engineer with 4 years of experience designing GenAI-enabled analytical frameworks and applied machine learning for regulated financial services. Builds data models and transformation pipelines in Python, SQL, PySpark, and Databricks, and leads prompt engineering and LLM fine-tuning with LangChain, LlamaIndex, and Hugging Face Transformers against accuracy, compliance, and ethical AI standards. Strong predictive modeling and experimentation record, including a 0.89 AUC-ROC credit risk model and a 22% reduction in false-positive compliance alerts at 95% recall. Translates model results and behavioral insights into executive storytelling through Power BI and Tableau across a $2B+ managed asset portfolio, aiming to bring production GenAI engineering and business-facing analytics to enterprise decision intelligence and AI product strategy.

Available to hire

AI/ML Engineer with 4 years of experience designing GenAI-enabled analytical frameworks and applied machine learning for regulated financial services. Builds data models and transformation pipelines in Python, SQL, PySpark, and Databricks, and leads prompt engineering and LLM fine-tuning with LangChain, LlamaIndex, and Hugging Face Transformers against accuracy, compliance, and ethical AI standards.

Strong predictive modeling and experimentation record, including a 0.89 AUC-ROC credit risk model and a 22% reduction in false-positive compliance alerts at 95% recall. Translates model results and behavioral insights into executive storytelling through Power BI and Tableau across a $2B+ managed asset portfolio, aiming to bring production GenAI engineering and business-facing analytics to enterprise decision intelligence and AI product strategy.

Skills

Experience Level

Expert

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Beginner

Beginner

Work Experience

AI Engineer at Wells Fargo

January 1, 2025 - Present

Built a multi-agent financial compliance auditing platform using CrewAI and LangGraph to automate regulatory risk assessment across institutional documents. Increased audit throughput by 34% and improved alert precision, cutting false positives by 22% while holding recall constant via evidence-grounded validation. Designed a Knowledge Graph + RAG pipeline (LlamaIndex, LLaMA, Pinecone) with an evaluation harness; achieved 94% retrieval recall@5 and 96% answer faithfulness while reducing retrieval latency by 180ms. Fine-tuned a BERT-family transformer with LoRA for NER on unstructured cross-border transaction logs, reaching 0.91 macro-F1 and reducing downstream processing time by 41%. Productionized a credit risk model on Azure AI Studio with LightGBM and TensorFlow behind a monitored inference endpoint with drift detection and scheduled retraining; improved AUC-ROC by ~14% and increased minority default recall.

Machine Learning Engineer at Tech Mahindra

August 1, 2021 - July 31, 2023

Fine-tuned BERT and applied knowledge distillation to a DistilBERT student model to automate ticket routing across 20,000+ monthly tickets, cutting triage time by 45% and validating with macro-F1, precision/recall, and confusion-matrix analysis. Deployed an XGBoost churn prediction model on AWS SageMaker at 87% accuracy to provide a ranked view of at-risk accounts, reducing churn by 12%. Built a forecasting system (ARIMA, Prophet, XGBoost) on AWS SageMaker over high-volume retail transactions, reducing forecast error to 26% WMAPE vs. a seasonal-naive baseline and decreasing stock outs. Segmented clients with PCA followed by K-Means and DBSCAN clustering on PySpark to identify 5 distinct customer personas across 2M+ active profiles, shaping downstream personalization. Engineered scalable ETL pipelines in Python, PySpark, and PostgreSQL over 10M+ records, cutting training-data preparation time by 40% and streaming validated features into Tableau dashboards.

ML Engineer at Tech Mahindra

August 1, 2021 - July 31, 2023

Fine-tuned pre-trained BERT models using LoRA/PEFT (Hugging Face) and NLTK for ticket-category classification, tracking macro-F1 in validation and reducing customer support ticket resolution time by 15 minutes. Deployed an enterprise demand forecasting system using ARIMA, Prophet, and XGBoost on AWS SageMaker, reducing forecast error (WMAPE) by 26% versus a seasonal-naive baseline and decreasing stockouts. Built a defect detection pipeline for manufacturing clients using Mask R-CNN and PyTorch, accelerating QA inspection by 38% while maintaining 94% precision and strong recall on structural anomalies. Implemented client segmentation using PCA + K-Means/DBSCAN on PySpark across 2M+ user profiles with silhouette and business KPI validation. Engineered scalable ETL pipelines in Python and PostgreSQL to clean/process unstructured logs and stream validated features into Tableau dashboards for executive performance tracking.