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I am a results-driven Senior AI-ML Engineer with 9+ years of experience turning research prototypes into production-grade ML systems across diverse enterprise environments. I excel at architecting end-to-end AI solutions, optimizing inference for critical applications, and embedding governance to ensure compliant, auditable AI deployments. I have built predictive models across genomic, clinical, and financial datasets, created reproducible training workflows with audit trails, and automated transitions from notebooks to production pipelines. I am passionate about scalable, cloud-based platforms, model monitoring, and collaborating with data engineers and domain experts to deliver reliable, explainable AI that business and clinical stakeholders can trust.…I am a results-driven Senior AI-ML Engineer with 9+ years of experience turning research prototypes into production-grade ML systems across diverse enterprise environments. I excel at architecting end-to-end AI solutions, optimizing inference for critical applications, and embedding governance to ensure compliant, auditable AI deployments. I have built predictive models across genomic, clinical, and financial datasets, created reproducible training workflows with audit trails, and automated transitions from notebooks to production pipelines. I am passionate about scalable, cloud-based platforms, model monitoring, and collaborating with data engineers and domain experts to deliver reliable, explainable AI that business and clinical stakeholders can trust.

Kovuru Hari kumar

Data Scientist, AI Engineer, AI Developer, +2

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I am a results-driven Senior AI-ML Engineer with 9+ years of experience turning research prototypes into production-grade ML systems across diverse enterprise environments. I excel at architecting end-to-end AI solutions, optimizing inference for critical applications, and embedding governance to ensure compliant, auditable AI deployments. I have built predictive models across genomic, clinical, and financial datasets, created reproducible training workflows with audit trails, and automated transitions from notebooks to production pipelines. I am passionate about scalable, cloud-based platforms, model monitoring, and collaborating with data engineers and domain experts to deliver reliable, explainable AI that business and clinical stakeholders can trust.…I am a results-driven Senior AI-ML Engineer with 9+ years of experience turning research prototypes into production-grade ML systems across diverse enterprise environments. I excel at architecting end-to-end AI solutions, optimizing inference for critical applications, and embedding governance to ensure compliant, auditable AI deployments. I have built predictive models across genomic, clinical, and financial datasets, created reproducible training workflows with audit trails, and automated transitions from notebooks to production pipelines. I am passionate about scalable, cloud-based platforms, model monitoring, and collaborating with data engineers and domain experts to deliver reliable, explainable AI that business and clinical stakeholders can trust.

Available to hire

I am a results-driven Senior AI-ML Engineer with 9+ years of experience turning research prototypes into production-grade ML systems across diverse enterprise environments. I excel at architecting end-to-end AI solutions, optimizing inference for critical applications, and embedding governance to ensure compliant, auditable AI deployments.

I have built predictive models across genomic, clinical, and financial datasets, created reproducible training workflows with audit trails, and automated transitions from notebooks to production pipelines. I am passionate about scalable, cloud-based platforms, model monitoring, and collaborating with data engineers and domain experts to deliver reliable, explainable AI that business and clinical stakeholders can trust.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Senior AI-ML Engineer at Johnson & Johnson

March 1, 2025 - Present

Led the design and deployment of an enterprise-grade AI-assisted clinical trial response intelligence platform. Trained deep learning models on multi-modal longitudinal patient data to support drug response prediction and patient cohort stratification, enabling near real-time insights for R&D teams. Implemented a centralized, versioned Feast feature store to standardize time-series patient features and guarantee consistency between offline training and online serving. Built an end-to-end MLOps workflow within Azure Machine Learning Pipelines to satisfy GxP requirements, including versioned datasets, model artifacts, and audit-ready metadata. Optimized prediction latency by leveraging Triton Inference Server ensembles for dynamic batching and concurrent serving of heterogeneous PyTorch and TensorFlow models. Secured sensitive artifacts via Azure Key Vault and Vault, and deployed stateless RESTful prediction microservices on AKS with OAuth2-based authentication. Established monitoring fo

AI-ML Engineer at IBM

August 1, 2023 - February 1, 2025

Designed and maintained a scalable enterprise ML platform enabling autonomous ML lifecycle management across multi-cloud and hybrid environments. Implemented dataset and model versioning with DVC to enable reproducible experiments and governance. Built end-to-end ML pipelines with MLflow for experiment tracking, packaging, and deployment, while containerizing workloads with Docker for consistent runtimes. Deployed multi-model inference pipelines on AWS SageMaker, with autoscaling, secure endpoint access, and structured logging. Exposed REST APIs for internal applications and analytics pipelines, and built secure, token-based authentication across services. Pioneered generative AI components for synthetic data generation and automated pipeline code generation, and integrated a predictive pipeline governance engine to recommend retraining and optimization decisions. Orchestrated preprocessing and feature store pipelines in collaboration with data engineering to ensure data quality and re

ML Engineer at Broadridge Financial Solutions

March 1, 2021 - July 1, 2023

Built a real-time regulatory reporting and predictive compliance platform by constructing robust data ingestion and feature pipelines with schema validation and data lineage. Enabled batch and near real-time risk scoring with zero data loss, and tracked experiments with MLflow to ensure reproducibility. Containerized XGBoost and scikit-learn models and deployed them on EKS with Triton for concurrent inference. Automated MLOps infrastructure with Terraform to ensure consistent, version-controlled deployments across dev, staging, and production. Developed CI/CD pipelines with automated testing and security scans, and created regulatory-compliant explainability reports embedding feature attributions for bias detection. Managed encrypted S3 data lakes with object versioning and lifecycle policies, and deployed distributed PyTorch training clusters on EC2 with optimized data access from S3. Implemented governance controls across ML workflows, including audit logging, key management, and rep

Data Scientist at LTI

April 1, 2016 - October 1, 2020

Developed predictive and risk-scoring models to support operational and financial decision making. Built scalable data processing workflows to handle large transaction and log datasets, significantly improving reliability and turnaround time for analysis. Collected, cleaned, and merged structured data using SQL to prepare reliable datasets for modeling and reporting. Built regression models to analyze financial trends and support business decision-making; automated data ingestion from internal and external systems; maintained clean training datasets in shared storage; created reusable data preparation steps that reduced effort across projects. Worked closely with business analysts to validate insights and translate technical findings into actionable recommendations. Presented results through reports and dashboards, enabling stakeholders to act on data-driven insights.