LLM Training & Serving
LLM Fine-tuningLoRA / QLoRAEvaluationOpenAI-Compatible Serving
Modelling & Analytical Methods
Classical MLDeep LearningComputer VisionNLPForecastingFeature EngineeringOperations ResearchAutoencoders
Frameworks & APIs
scikit-learnXGBoostPyTorchTensorFlowHugging Face / PEFTUnslothvLLMOR-Tools
GPU & Distributed Computing
Multi-GPU TrainingRAPIDS cuDF / CuPy
Model Lifecycle
MLflowEvaluation / RegistryRetrainingVertex AI / Azure ML PipelinesFeature Store
Cloud & Deployment
GCP / AzureGKE / KubernetesDockerCloud Run / FunctionsAzure Functions / Logic AppsHelm / Istio
Reliability & Reporting
CI/CDCloud BuildArgoCD / GitOpsPrometheus / GrafanaMonitoring / Load TestingStreamlit / Power BI
Languages, Data & Storage
PythonSQLBeam / DataflowPub/SubBigQueryRedisGCS / Azure BlobPandas / NumPyDaskGit / Linux
Certifications
Google CloudCertified Generative AI Leader
Microsoft CertifiedAzure AI Engineer Associate
Microsoft CertifiedAzure Data Scientist Associate
Education
B.E. Electrical & Electronics
Andhra University · 2012–2016 · 80%
Selected Recognition
Best Buy — Talent Quotient (2026)
Best Buy client — AML Hall of Fame (2024, Wipro engagement)
Lead AI and ML engineer and data scientist with 10+ years of experience, building production AI/ML/LLM systems. Leads end-to-end AI delivery, combining hands-on model development with technical leadership to turn business problems into scalable, high-throughput, low-latency production systems. Experience spans predictive modelling, forecasting, operations research, computer vision, and generative AI across retail, cybersecurity, manufacturing, insurance, and supply-chain optimization.
Experience
Lead Artificial Intelligence Engineer
Best Buy | Jul 2025 – Present
- Productionized a reusable LLM fine-tuning framework using LoRA/QLoRA and deployed vLLM-based inference serving on GKE, with estimated annual API-cost savings of ~$300K. Kept inputs company-managed and reduced external API exposure at peak demand.
- Built batch/streaming/real-time fraud systems: 40,000 feature events/sec at peak. Fraud ML saved US$1.5M/year. Holiday fraud-score coverage improved ~20%.
- Lead architecture and production delivery of reusable ML and LLM systems; partner with data scientists on secure, monitored services.
Lead ML Engineer — ML Engineering & Operations
Wipro | Aug 2023 – Jul 2025
- Engineered AWS account digital fingerprinting with GPU-accelerated RAPIDS cuDF/CuPy training/inference on DGX (8×A100); per-entity autoencoders learned behavioral fingerprints from billion-row AWS datasets spanning 20+ days.
- Scaled Proofpoint phishing detection to 2,400 emails/sec (2× throughput); incorporated security-team feedback and Sentinel integration to accelerate quarantine.
- Automated abuse-inbox analysis with OCR and ML routing, doubling case volume; routed evidence to partners for takedowns.
- Mentored ML/MLOps engineers; screened 300+ résumés, conducted 50+ technical interviews, and coordinated client/NVIDIA delivery.
Senior Data Scientist — Data Science / Azure ML
Accenture | May 2021 – Sep 2023
- Developed product-quality prediction for BamaGruppen with fully automated training and serving using Logic Apps, Azure ML pipelines, model registry and container deployments: $2.5M/year saved; 130 to 160 truck inspections/day; +17% defect detection; +20% customer approval.
- Replaced manual Excel planning with automated last-mile routing and transport optimization using OR-Tools and mixed-integer models, integrating Azure Functions, Logic Apps and RPA to enable rapid replanning and improve delivery efficiency.
- Evaluated cost, freshness, carbon and hub-placement scenarios; mentored data scientists and advised Norwegian stakeholders.
Data Scientist
GD Research Centre | May 2020 – May 2021
- Developed domain-aware forecasts for GlobalData across 15+ industry verticals for enterprise market-intelligence decisions.
Deep Learning Engineer
Tata Consultancy Services | Jul 2019 – Mar 2020
- Built and deployed an end-to-end semiconductor ML system: distributed training on ~1 million images in ~3 hours; 90% classification accuracy. Deployed at Amkor, South Korea, and trained the client team.
Senior Software Engineer — ML
Infosys | May 2016 – Jul 2019
- Implemented opportunity scoring using logistic regression, with Power BI reporting for sales prioritization. Delivered tested ID-card generation workflows and shared knowledge with the team.