.png){kind=logo}
Vetted TensorFlow Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in Generative AI, NLP, and RAG systems
Mid-level Software Engineer specializing in Python automation and GenAI on AWS
Junior Machine Learning Engineer specializing in Generative AI and LLM agents
Entry-Level Full-Stack Engineer specializing in backend APIs and cloud architectures
Mid-level AI & Data Science professional specializing in MLOps, deep learning, and UAV research
Junior Full-Stack Developer specializing in AI integrations and LLM research
Mid-level AI/ML Research Engineer specializing in NLP, LLM agents, and multimodal systems
Mid-Level Full-Stack Software Engineer specializing in AI automation and RAG agents
Mid-level AI/ML Engineer specializing in GenAI, agentic AI, and RAG pipelines
Mid-level Data Engineer specializing in cloud-native batch and streaming pipelines
Junior Full-Stack Developer specializing in Django/React and cloud-native APIs
Intern software engineer specializing in AI, data science, and full-stack development
Intern Software Engineer specializing in backend, AI, and full-stack web systems
Haeshitha Indukuri
Entry AI/ML Engineer specializing in Generative AI, LLMs, and MLOps
“Built and productionized a MediCloud/Medicoud LLM microservice platform that lets clinicians query medical data in natural language, orchestrating multi-step RAG-style workflows with LangChain and evaluating/debugging with LangSmith. Delivered measurable gains (consistency ~70%→90% / +20%; latency ~2.0s→1.1s / -40%) by implementing structured prompts, fallback logic across multiple LLMs, hybrid retrieval tuning, and AWS Lambda performance optimizations (package size, async, caching).”
“Full-stack AI engineer who has built and deployed multiple end-to-end LLM products, including an AI interview assistant, a multi-agent market research platform, and a policy document explainer. Particularly strong in productionizing agentic workflows, integrating tools like Whisper, Tavus, LiveKit, CrewAI, and LangGraph, and hardening messy real-world AI/document pipelines with validation, memory isolation, and fallback handling.”
Mid-level Generative AI & ML Engineer specializing in LLMs, RAG, and MLOps
Jaiden Kettleson
Entry-Level Full-Stack & AI Engineer specializing in chatbots and web apps
“Data Science honors graduate (Maryville University) who has built Python/SQL backends and a capstone website handling sensitive user data. Emphasizes secure data handling (password encryption, secure database updates) and uses Git/GitHub Pages with CI/CD-style practices for managing and deploying changes.”
Md Rifat Ullah
Mid-level AI/ML Engineer specializing in NLP, GenAI, and conversational AI
“Built and deployed a production bilingual (Bengali/English) AI virtual assistant that replaced IVR for telecom customer service at massive scale (~15M users), integrating ASR/TTS, Rasa dialogue management, and custom NLP. Overcame low-resource Bengali data and noisy call-center audio with synthetic data augmentation and transformer fine-tuning, achieving significant production gains including ~50% reduction in support calls.”
Muhammad Murtaza Murtaza
Mid-level Machine Learning Engineer specializing in NLP, Computer Vision & Predictive Analytics
“Built a production LLM fine-tuning pipeline for domain-specific code generation at Pigeonbyte Technologies, including automated collection and rigorous quality filtering of 10M+ code samples (AST validation, sandbox execution/testing, deduplication, drift monitoring, and human-in-the-loop review). Also implemented end-to-end ML orchestration in Apache Airflow with data quality gates, dataset versioning in S3, benchmarking, and automated model promotion, and has a reliability-first approach to agent/workflow design.”