# Venkata K

> AI/ML Engineer at IBM

Profile: https://flows.cv/venkatak

## Work Experience
### AI/ML Engineer @ IBM
Jan 2024
● Built scalable machine learning pipelines using PySpark and Airflow for real-time clickstream data, improving  recommendation accuracy by 22%.
● Designed and deployed low-latency inference systems using PyTorch, TorchServe, and Kubernetes, achieving 2x faster API response times and reducing infrastructure costs.
● Developed advanced recommendation systems leveraging RAG, vector search (FAISS), and LLMs, increasing upsell conversion rates by 15%.
● Implemented multi-agent AI workflows using LangGraph and LlamaIndex to enhance contextual understanding and response relevance in LLM-powered applications.
● Engineered real-time streaming pipelines with Kafka and Spark Streaming, improving anomaly detection coverage by 60% and enabling proactive user engagement insights.
● Optimized distributed model training using PyTorch Lightning and mixed precision techniques, improving training performance by 40%.
● Automated end-to-end ML workflows using MLflow and AWS SageMaker, reducing deployment downtime by 70% and ensuring continuous model freshness.
● Migrated and scaled ML infrastructure on AWS (EKS, Terraform), reducing deployment time from hours to under 20 minutes through robust CI/CD pipelines.

### Machine Learning Engineer @ Evernorth Health Services
Jan 2021 – Jan 2022 | Hyderabad
● Unified 50TB+ of EHR and claims data by developing PySpark ETL pipelines that cut data preparation time by 35%, giving the team faster access to reliable clinical datasets.
● Improved the quality of patient insights by fine-tuning a BERT-based medical NLP model on 500K+ unstructured EHR notes, increasing the availability of meaningful features by 40%.
● Built a disease-risk prediction model in TensorFlow that delivered an AUC of 0.91, helping healthcare teams identify chronic-condition risks earlier and with greater accuracy.
● Increased transparency and clinician trust by integrating SHAP explainability and ensuring HIPAA-aligned audit trails, which encouraged a 20% boost in AI-driven decision usage.
● Designed an efficient MLOps workflow using Azure DevOps and MLflow that improved model versioning and reduced deployment cycles to just 48 hours.
● Deployed ML models as Docker microservices managed through Kubernetes, using FHIR-compatible APIs to maintain sub-200ms inference latency for 10,000+ healthcare professionals.
● Ran bias analysis and mitigation across demographic groups, reducing prediction gaps by 15% and aligning the models with Responsible AI guidelines.
● Cut cloud compute costs by 70% by applying model quantization and leveraging TensorRT for faster, hardware-optimized inference.
● Built a RASA-based triage assistant that responds to 20,000+ patient queries per day, helping care teams focus on urgent and high-complexity cases.
● Created secure, HIPAA-compliant Power BI dashboards that turned model outputs into clear public-health insights, guiding a $5M annual intervention strategy.

### Machine Learning Engineer @ JPMorganChase
Jan 2020 – Jan 2021 | Bengaluru
● Developed end-to-end NLP and LLM solutions to process 8M+ SWIFT payment messages using BERT and RAG-based pipelines, improving classification accuracy from 72% to 91% and reducing manual investigation effort.
● Built and deployed real-time fraud detection and anomaly detection systems using Kafka, PySpark, and SageMaker, reducing fraud latency from 2.3s to 0.8s and lowering false positives by 40%.
● Delivered significant financial impact by improving loan approval accuracy by 28% and reducing default risk by $4.1M through scalable credit risk and prediction models.
● Designed production-grade ML pipelines and inference systems using AWS SageMaker, MLflow, Docker, and ECS, enabling reliable processing of 120K+ transactions per day with low-latency predictions.
● Enhanced operational efficiency by implementing LLM-powered assistants and RAG-based summarization systems, reducing analyst triaging time by 35% and improving compliance and decision-making workflows.


## Education
### Master's degree
IWU National & Global


## Contact & Social
- LinkedIn: https://linkedin.com/in/venkatareddy-ai
- Email: mailto:venkatareddyk3138@gmail.com

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Source: https://flows.cv/venkatak
JSON Resume: https://flows.cv/venkatak/resume.json
Last updated: 2026-04-17