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I am a Senior AI/ML Engineer with 8+ years of experience designing, building, and deploying production-grade machine learning and Generative AI systems. I have led initiatives across banking, insurance, healthcare, and regulated enterprise environments, with a focus on Retrieval-Augmented Generation, knowledge systems, fraud detection, and scalable data engineering. I own end-to-end AI lifecycles—from data ingestion and feature engineering to model deployment, monitoring, governance, and compliance. I work closely with product, compliance, legal, and risk teams to deliver accurate, explainable, auditable AI outputs, and I mentor teams on best practices in production-grade AI and Generative AI.…I am a Senior AI/ML Engineer with 8+ years of experience designing, building, and deploying production-grade machine learning and Generative AI systems. I have led initiatives across banking, insurance, healthcare, and regulated enterprise environments, with a focus on Retrieval-Augmented Generation, knowledge systems, fraud detection, and scalable data engineering. I own end-to-end AI lifecycles—from data ingestion and feature engineering to model deployment, monitoring, governance, and compliance. I work closely with product, compliance, legal, and risk teams to deliver accurate, explainable, auditable AI outputs, and I mentor teams on best practices in production-grade AI and Generative AI.

Krishna Reddy

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I am a Senior AI/ML Engineer with 8+ years of experience designing, building, and deploying production-grade machine learning and Generative AI systems. I have led initiatives across banking, insurance, healthcare, and regulated enterprise environments, with a focus on Retrieval-Augmented Generation, knowledge systems, fraud detection, and scalable data engineering. I own end-to-end AI lifecycles—from data ingestion and feature engineering to model deployment, monitoring, governance, and compliance. I work closely with product, compliance, legal, and risk teams to deliver accurate, explainable, auditable AI outputs, and I mentor teams on best practices in production-grade AI and Generative AI.…I am a Senior AI/ML Engineer with 8+ years of experience designing, building, and deploying production-grade machine learning and Generative AI systems. I have led initiatives across banking, insurance, healthcare, and regulated enterprise environments, with a focus on Retrieval-Augmented Generation, knowledge systems, fraud detection, and scalable data engineering. I own end-to-end AI lifecycles—from data ingestion and feature engineering to model deployment, monitoring, governance, and compliance. I work closely with product, compliance, legal, and risk teams to deliver accurate, explainable, auditable AI outputs, and I mentor teams on best practices in production-grade AI and Generative AI.

Available to hire

I am a Senior AI/ML Engineer with 8+ years of experience designing, building, and deploying production-grade machine learning and Generative AI systems. I have led initiatives across banking, insurance, healthcare, and regulated enterprise environments, with a focus on Retrieval-Augmented Generation, knowledge systems, fraud detection, and scalable data engineering.

I own end-to-end AI lifecycles—from data ingestion and feature engineering to model deployment, monitoring, governance, and compliance. I work closely with product, compliance, legal, and risk teams to deliver accurate, explainable, auditable AI outputs, and I mentor teams on best practices in production-grade AI and Generative AI.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

Senior AI/ML Engineer at Comerica Bank

November 1, 2024 - Present

Led the development of an enterprise-scale Generative AI knowledge assistant to enable secure, document-grounded question answering across financial, risk, and compliance domains. Designed and implemented a Retrieval-Augmented Generation pipeline combining semantic vector retrieval with enterprise-approved LLMs to deliver accurate, auditable responses. Built scalable document ingestion pipelines, applied text preprocessing and semantic chunking, and created embedding-generation workflows for dense vector representations. Implemented embedding-based retrieval, prompt templating/versioning, and integration of enterprise metadata to produce traceable outputs. Deployed GenAI as FastAPI-based microservices, established governance (PII masking, RBAC, audit logging), and built monitoring/observability with Grafana. Collaborated with product, compliance, legal, and risk teams and mentored engineers on production-grade GenAI practices.

Machine Learning Engineer at GEICO

February 1, 2023 - October 1, 2024

Developed an enterprise fraud-detection platform to identify suspicious insurance claims and reduce losses. Built end-to-end ML pipelines, trained classifiers (Logistic Regression, Random Forest, XGBoost), and engineered fraud-related features from claims history, demographics, policy attributes, accident metadata, temporal patterns, and payment behavior. Addressed class imbalance, tuned thresholds with fraud operations, and deployed batch inference REST APIs for near-real-time risk scoring. Integrated outputs into claims workflows, implemented monitoring for drift, and provided explainability (feature importance, rule-based reason codes). Supported A/B testing and ensured data quality and governance in regulated environments.

Data Scientist at S&P Global

December 1, 2019 - July 1, 2022

Imported large volumes of structured transactional data into data lake environments and contributed to HSBC GBM data modernization. Designed batch/micro-batch ingestion pipelines with Spark (PySpark) and SQL, built data transformations/enrichment to standardize schemas, and supported the GBM Big Data Lake across 300+ internal systems. Evaluated Delta Lake features in Azure Databricks, built secure/anonymized data views, and optimized Spark jobs. Collaborated with risk analysts and reporting teams to deliver analytics-ready datasets and documented data flows for governance and audits.

Data Engineer at Flutter Entertainment

August 1, 2017 - November 1, 2019

Designed and implemented large-scale batch ETL pipelines for sportsbook betting transactions, odds updates, settlements, and customer activity. Built ingestion workflows with Sqoop and file transfers into HDFS, modeled raw/curated/aggregated data in Hive, and developed Spark batch jobs for multi-granularity views. Implemented partitioning/bucketing, tuned performance, and created reusable data processing frameworks. Generated daily/weekly/monthly aggregates for business, risk, and compliance, automated batch workflows, and supported regulatory/audit reporting with complete data lineage.