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Vetted Deep Learning Professionals
Pre-screened and vetted.
Vijayagopalan Raveendran
Principal Enterprise Architect specializing in AI, cloud, data, and FinTech transformation
“Solutions/technical consulting professional with enterprise experience supporting major accounts including Costco, MasterCard, Delta Dental of Michigan, and Fannie Mae. Brings a blend of cloud migration, enterprise architecture, security/IAM integration, and business-case development, plus hands-on automation work in Python and GCP to modernize sales-related data processing.”
Kaival Shah
Intern Software Engineer specializing in cloud, backend, and ML systems
“Full-stack builder with hands-on experience spanning a MERN e-commerce product, an AI code review agent, and an ambiguous AWS internship project involving PyTorch/TensorFlow support in Redshift. Particularly interesting for recruiters because they combine product-minded engineering with AI agent reliability work, including CI/CD integration, telemetry via Weights & Biases, and measurable impact like 80% reduction in manual review effort.”
Moh Abdullah
Senior AI/ML Engineer specializing in Generative AI, LLMs, and production ML systems
“ML/AI engineer with hands-on ownership of both classical ML and GenAI systems in production. They built an end-to-end churn prediction service on AWS and also shipped RAG-based document search/summarization features, with clear experience in monitoring, hallucination reduction, cost/latency optimization, and creating shared Python/LLM infrastructure used across teams.”
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.”
Junior Software Engineer specializing in Python full-stack, cloud/DevOps, and AI/ML
Mid-Level Software Engineer specializing in cloud platforms and agentic AI automation
Intern Software & Data Engineer specializing in ML, robotics, and computer vision
Mid-Level Full-Stack Software Engineer specializing in web platforms and AI research
Intern Software Engineer specializing in machine learning and cloud systems
Mid-level Full-Stack Engineer specializing in cloud-native microservices and AI/ML
Intern Software Engineer specializing in systems, embedded Android, and ML
Intern Deep Learning Engineer specializing in LLM agents and on-device multimodal inference
Mid-Level Software Developer specializing in AI backend systems and distributed computing
Junior Software Engineer specializing in full-stack web and ML systems
Staff AI Engineer specializing in geospatial and remote sensing machine learning
Mid-level Data Scientist specializing in financial risk, fraud detection, and GenAI NLP
Junior Software Developer specializing in AWS backend systems and web applications
Mid-level Data Scientist specializing in NLP, GenAI, and time-series modeling
Intern Software Engineer specializing in full-stack and machine learning