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Vetted Model Deployment Professionals
Pre-screened and vetted.
Keerthana Tammina
Mid-level Data Scientist specializing in machine learning and generative AI
“ML/LLM engineer who has shipped a production transformer-based document understanding system on AWS, owning the full pipeline from domain fine-tuning to Dockerized CI/CD deployment. Demonstrates strong production rigor—latency optimization (distillation/quantization, async batching, autoscaling), orchestration with Airflow/Step Functions/Azure Data Factory, and monitoring/drift detection—plus experience translating ops stakeholder needs into adopted AI automation via dashboards.”
Akhilesh Padala
Mid-level AI/ML Engineer specializing in Generative AI, NLP, and Computer Vision
“ML/AI engineer with strong end-to-end production ownership across predictive ML and Generative AI use cases. They built a churn prediction platform that cut churn 12% and preserved about $1.2M in annual revenue, and also shipped a RAG-based support assistant that reduced ticket resolution time 30% while improving agent satisfaction and onboarding speed.”
“ML/AI engineer with strong end-to-end production ownership across classical ML and GenAI systems. Built and deployed predictive analytics and RAG-based internal tools on AWS/Kubernetes with measurable impact on accuracy, latency, deployment speed, safety, and user productivity.”
Rajeshwar Ragupatula
Director-level AI Architect/Manager specializing in GenAI, MLOps, and enterprise automation
“GenAI/ML engineering leader (player-coach) who built and deployed an image-to-text production system for topology/resource diagrams, combining YOLO-based issue detection with an LLM to generate support-ready reports at scale. Heavy AWS stack (SageMaker, Step Functions, Lambda, CloudWatch, FastAPI, Kubernetes/Docker) with KPI-driven optimization (MTTR, P50), including ~21 custom labels and reported 30–50% faster issue identification while processing thousands of images in production.”
Mid-level MLOps/DevOps Engineer specializing in cloud automation and ML pipelines
Mid-level AI Engineer specializing in Generative AI, LLMs, and RAG systems
Mid-level AI Software Engineer specializing in LLM agents and workflow orchestration
Mid-Level Software Engineer specializing in cloud-native microservices and real-time data pipelines
Mid-Level Software Engineer specializing in distributed systems and cloud data pipelines
Senior technology transformation leader specializing in cloud, AI, and governance
Mid-level Full-Stack Engineer specializing in cloud-native and AI-driven systems
Mid-Level Software Developer specializing in AI backend systems and distributed computing
Executive engineering leader specializing in computer vision, AI, and real-time systems
Intern Software Engineer specializing in full-stack and machine learning
Mid-level AI/ML Engineer specializing in LLMs and document intelligence
Mid-Level Java Developer specializing in microservices and AI/ML integration
Principal Technology Architect specializing in Salesforce Data Cloud, integrations, and agentic AI
Mid-level Machine Learning Engineer specializing in NLP, recommender systems, and MLOps
Mid-level Machine Learning Engineer specializing in MLOps, NLP, and quantitative trading