.png){kind=logo}
Vetted Natural Language Processing Professionals
Pre-screened and vetted.
Tharun Chowdary Malepati
Mid-level AI/ML Engineer specializing in GenAI, NLP, and production MLOps
“AI/LLM engineer who built and deployed a production healthcare RAG chatbot ("DoctorBot") with strict medical safety guardrails, an 85% confidence-gated verification layer, and latency optimizations that cut responses from ~8s to ~2–3s. Also worked on finflow.ai to generate finance/banking test cases from BRDs, collaborating closely with non-technical domain stakeholders, and has hands-on orchestration experience with LangChain/LangGraph and agentic evaluation/monitoring practices.”
“Built a production AI-powered university marking system that automates question generation and grading from PDF course materials using a RAG pipeline (S3 + Pinecone) orchestrated with LangChain/LangGraph and deployed on AWS ECS via Docker/ECR and GitHub Actions CI/CD. Addressed a key real-world LLM challenge—grading consistency—by implementing rubric-based scoring, retrieval re-ranking, and standardized context summarization, validated against human instructors.”
Suma Mallu
Intern Full-Stack Software Engineer specializing in UI/UX and AI-integrated web apps
“Built and owned Python backend APIs for real-time educational dashboards at ASU’s Machine Learning lab, improving responsiveness by cutting latency ~35% through caching, batching, and profiling-driven optimizations. Has hands-on experience containerizing Node.js/Python services and running GitOps-style CI/CD with GitHub Actions, plus supporting smaller infrastructure transitions with reproducible, portable configs.”
Ahmad Alomari
Senior Data Scientist & Machine Learning Engineer specializing in computer vision and production ML
“PhD in computer engineering who has built production-oriented ML/NLP systems for space-weather prediction using Spark-based ETL on noisy satellite sensor logs. Strong in entity resolution and semantic search—fine-tuned E5 embeddings with contrastive learning and deployed to Pinecone, improving top-5 retrieval precision by 25%—and emphasizes scalable, observable pipelines with Airflow, Docker, and CI/CD.”
Intern Full-Stack Software Engineer specializing in web apps, APIs, and OCR/LLM automation
Senior AI Product Manager specializing in ML-driven personalization and generative AI
Mid-level Generative AI Engineer specializing in LLMs and RAG for enterprise and FinTech
Mid-level Full-Stack Software Engineer specializing in microservices and web applications
Senior AI/ML Engineer specializing in Generative AI, NLP, and MLOps
Senior Full-Stack Software Engineer specializing in distributed systems and AI platforms
Mid-level Full-Stack Engineer specializing in web/mobile apps and AI (RAG/GraphRAG)
Mid-Level Full-Stack Software Engineer specializing in cloud web apps and Microsoft Dynamics 365
Junior Machine Learning Engineer specializing in computer vision and LLM/VLM systems
Mid-level Full-Stack Developer specializing in web, mobile, and cloud deployments
Mid-Level Software Engineer specializing in backend systems, cloud, and LLM/NLP applications
Senior Software Engineer specializing in Python, cloud microservices, and AI/voice analytics
Junior Backend Engineer specializing in Python, cloud-native systems, and data streaming
Junior AI/ML Engineer specializing in deep learning and reinforcement learning systems
Senior Machine Learning Engineer specializing in computer vision, NLP, and LLM applications
Entry-Level AI/ML Engineer specializing in LLM apps and RAG pipelines
Senior Full-Stack Python Engineer specializing in cloud-native web apps and ML