Lead AI/ML Engineer & Data Scientist | Production ML & GenAI | Distributed Systems | GCP · Azure · GPU Computing

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.

Skills

- LLM Training & Serving: LLM Fine-tuning; LoRA / QLoRA; Evaluation; OpenAI-Compatible Serving

- Modelling & Analytical Methods: Classical ML; Deep Learning; Computer Vision; NLP; Forecasting; Feature Engineering; Operations Research; Autoencoders

- Frameworks & APIs: scikit-learn; XGBoost; PyTorch; TensorFlow; Hugging Face / PEFT; Unsloth; vLLM; OR-Tools

- GPU & Distributed Computing: Multi-GPU Training; RAPIDS cuDF / CuPy

- Model Lifecycle: MLflow; Evaluation / Registry; Retraining; Vertex AI / Azure ML Pipelines; Feature Store

- Cloud & Deployment: GCP / Azure; GKE / Kubernetes; Docker; Cloud Run / Functions; Azure Functions / Logic Apps; Helm / Istio

- Reliability & Reporting: CI/CD; Cloud Build; ArgoCD / GitOps; Prometheus / Grafana; Monitoring / Load Testing; Streamlit / Power BI

- Languages, Data & Storage: Python; SQL; Beam / Dataflow; Pub/Sub; BigQuery; Redis; GCS / Azure Blob; Pandas / NumPy; Dask; Git / Linux

Experience

- 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.

- 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.

- 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.

- Developed domain-aware forecasts for GlobalData across 15+ industry verticals for enterprise market-intelligence decisions.

- 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.

- 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.

Certifications

- Google Cloud Certified: Generative AI Leader | Microsoft Certified: Azure AI Engineer Associate

- Microsoft Certified: Azure Data Scientist Associate

Education

B.E. Electrical & Electronics | Andhra University, Visakhapatnam | 2012 - 2016 · 80%