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I’m Bhavani Mulakala, a Senior Generative AI & Machine Learning Engineer with 10+ years of experience building scalable, production-grade AI/ML and LLM solutions in regulated enterprise environments. I’ve delivered end-to-end systems across fraud and payments, AML/KYC, healthcare claims and care management, government workforce and public benefits analytics, and telecom network analytics—balancing accuracy, performance, and compliance. I specialize in LLM engineering and GenAI pipelines, including RAG/GraphRAG, multi-agent orchestration, prompt engineering, and fine-tuning (LoRA/QLoRA, PEFT, SFT, RLHF/DPO). I also build reliable MLOps/LLMOps practices with strong evaluation and monitoring (offline metrics and groundedness/hallucination checks, MLflow, Prometheus/Grafana/CloudWatch), helping teams take models from prototype to production at large scale.…I’m Bhavani Mulakala, a Senior Generative AI & Machine Learning Engineer with 10+ years of experience building scalable, production-grade AI/ML and LLM solutions in regulated enterprise environments. I’ve delivered end-to-end systems across fraud and payments, AML/KYC, healthcare claims and care management, government workforce and public benefits analytics, and telecom network analytics—balancing accuracy, performance, and compliance. I specialize in LLM engineering and GenAI pipelines, including RAG/GraphRAG, multi-agent orchestration, prompt engineering, and fine-tuning (LoRA/QLoRA, PEFT, SFT, RLHF/DPO). I also build reliable MLOps/LLMOps practices with strong evaluation and monitoring (offline metrics and groundedness/hallucination checks, MLflow, Prometheus/Grafana/CloudWatch), helping teams take models from prototype to production at large scale.

Bhavani Mulakala

Data Scientist, AI Engineer, Data Engineer, +2

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I’m Bhavani Mulakala, a Senior Generative AI & Machine Learning Engineer with 10+ years of experience building scalable, production-grade AI/ML and LLM solutions in regulated enterprise environments. I’ve delivered end-to-end systems across fraud and payments, AML/KYC, healthcare claims and care management, government workforce and public benefits analytics, and telecom network analytics—balancing accuracy, performance, and compliance. I specialize in LLM engineering and GenAI pipelines, including RAG/GraphRAG, multi-agent orchestration, prompt engineering, and fine-tuning (LoRA/QLoRA, PEFT, SFT, RLHF/DPO). I also build reliable MLOps/LLMOps practices with strong evaluation and monitoring (offline metrics and groundedness/hallucination checks, MLflow, Prometheus/Grafana/CloudWatch), helping teams take models from prototype to production at large scale.…I’m Bhavani Mulakala, a Senior Generative AI & Machine Learning Engineer with 10+ years of experience building scalable, production-grade AI/ML and LLM solutions in regulated enterprise environments. I’ve delivered end-to-end systems across fraud and payments, AML/KYC, healthcare claims and care management, government workforce and public benefits analytics, and telecom network analytics—balancing accuracy, performance, and compliance. I specialize in LLM engineering and GenAI pipelines, including RAG/GraphRAG, multi-agent orchestration, prompt engineering, and fine-tuning (LoRA/QLoRA, PEFT, SFT, RLHF/DPO). I also build reliable MLOps/LLMOps practices with strong evaluation and monitoring (offline metrics and groundedness/hallucination checks, MLflow, Prometheus/Grafana/CloudWatch), helping teams take models from prototype to production at large scale.

Available to hire

I’m Bhavani Mulakala, a Senior Generative AI & Machine Learning Engineer with 10+ years of experience building scalable, production-grade AI/ML and LLM solutions in regulated enterprise environments. I’ve delivered end-to-end systems across fraud and payments, AML/KYC, healthcare claims and care management, government workforce and public benefits analytics, and telecom network analytics—balancing accuracy, performance, and compliance.

I specialize in LLM engineering and GenAI pipelines, including RAG/GraphRAG, multi-agent orchestration, prompt engineering, and fine-tuning (LoRA/QLoRA, PEFT, SFT, RLHF/DPO). I also build reliable MLOps/LLMOps practices with strong evaluation and monitoring (offline metrics and groundedness/hallucination checks, MLflow, Prometheus/Grafana/CloudWatch), helping teams take models from prototype to production at large scale.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

Senior Data Scientist (Gen AI) at Mastercard

March 1, 2023 - Present

Architected and deployed 15+ production-grade GenAI/LLM applications for payment processing, fraud operations, merchant servicing, and regulatory compliance. Built enterprise AI agents using Copilot Studio, Azure OpenAI, Semantic Kernel, LangGraph/LangChain, and MCP with RAG, planning/reasoning, tool calling, REST integrations, and human-in-the-loop workflows for payment investigations. Engineered fraud/AML ML pipelines and real-time streaming analytics to reduce fraud alert latency and improve detection accuracy, and delivered secure, PCI-DSS-aligned platforms with PII masking, encryption, RBAC, audit logging, and guardrails. Implemented scalable LLM evaluation (RAGAS, BLEU/ROUGE/BERTScore, groundedness/hallucination metrics) and used LangSmith for tracing and observability across 150+ workflows; fine-tuned Llama 3/Mistral/other models with LoRA/QLoRA and distributed training. Built REST APIs and intelligent document processing (OCR, NER, embeddings) and established automated monitori

AI / ML Engineer at Aetna

July 1, 2020 - February 1, 2023

Designed and deployed 30+ end-to-end ML models for claims prediction, fraud detection, prior authorization automation, care management, provider network optimization, and member risk stratification. Built healthcare NLP pipelines for extracting clinical insights from notes and records using SpaCy/NLTK and transformer-based NER/classification; engineered feature pipelines at large scale with Spark/Databricks/Delta Lake. Developed healthcare fraud and risk adjustment (including HCC) models, and created real-time inference APIs with FastAPI/Flask/Kubernetes/AKS and caching for high availability and low latency. Implemented comprehensive MLOps/SDLC including model versioning, experiment tracking, drift monitoring, retraining pipelines, data validation, canary/blue-green deployments, and rollback strategies. Built forecasting models for costs, utilization, readmissions, and pharmacy/premium trends; ensured HIPAA/PHI/PII and broader compliance controls. Partnered with clinical informatics, a

Machine Learning Engineer at State of Nebraska

April 1, 2018 - June 1, 2020

Developed end-to-end ML solutions for state agencies covering citizen services, public administration, workforce analytics, healthcare programs, and social service delivery. Built supervised/unsupervised predictive models for Medicaid eligibility, unemployment forecasting, public assistance fraud detection, tax forecasting, and resource allocation using Python, Spark/Hadoop, and common ML libraries. Implemented robust NLP solutions for government document/citizen feedback processing using NLTK/SpaCy, TF-IDF, Word2Vec/GloVe, sentiment/topic modeling, and NER with strong classification performance. Developed time-series forecasting models (ARIMA/SARIMA/Prophet/LSTM) for budget and operational planning. Established scalable training, validation, deployment, monitoring, and drift detection using MLflow, Docker, Kubernetes, CI/CD, and REST APIs; supported AWS and hybrid deployments. Built large-scale ETL/data preprocessing pipelines (12TB+), applied governance/security controls (RBAC, encry

Data Scientist at Cisco

May 1, 2016 - March 1, 2018

Built predictive analytics for telecom network traffic to improve anomaly detection and reduce downtime. Implemented ML models for network fault prediction, churn analysis, and customer behavior modeling using regression/classification/clustering approaches. Created scalable data pipelines and ETL workflows using Spark/Hadoop/Hive and Kafka to process large volumes of logs and telecom streaming data. Developed real-time analytics for latency/packet loss/bandwidth/QoS monitoring using streaming frameworks. Applied NLP on support tickets/service complaints for sentiment analysis and issue categorization. Partnered with engineering/DevOps teams to integrate models into monitoring systems and deploy solutions with MLOps practices, performance tuning, and cloud-based scalability.

Data Analyst at MetLife

February 1, 2014 - April 1, 2016

Supported life insurance, annuities, and group benefits analytics with policy administration and claims/business reporting. Extracted and analyzed insurance datasets using SQL/PL-SQL and advanced Excel to produce actionable insights. Built and maintained Tableau/Power BI/SSRS dashboards tracking KPIs such as claims adjudication time, policy lapse rate, premium collections, and enrollment trends. Assisted with fraud investigation by identifying anomalies and improving investigation efficiency; supported underwriting analytics and risk segmentation using actuarial datasets. Developed/optimized ETL processes using SSIS to integrate data from policy/claims systems and external sources. Conducted data validation/reconciliation across systems for reporting integrity and compliance with standards like EDI X12 and HIPAA-related requirements.