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Vetted Unsupervised Learning Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP
Senior Data Scientist / ML Engineer specializing in NLP, speech AI, and computer vision
Mid-level AI/ML Engineer specializing in Generative AI, NLP, and RAG 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).”
Jeevan Kumar
Mid-level Full-Stack AI Engineer specializing in LLM systems and RAG
“Built and shipped a production "Campaign AI" multi-agent system (LangGraph) that personalizes B2B outbound emails at scale using Apollo.io prospect data, clustering-based segmentation, and 21 persona variants. Notably uncovered that high click rates were largely email security scanners and created a validated bot-detection/scoring pipeline (timestamps/IP/user-agent/click patterns), bringing reported engagement down from ~40% to a trusted 5–8% that aligned with real conversions.”
Junior Software/AI Engineer specializing in LLM agents and RAG systems
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.”
MUHAMMAD KHUSHAL KHAN
Mid-level Quantitative Developer specializing in low-latency trading systems
“Backend/ML engineer with deep fintech and marketplace experience: built a real-time financial analytics + algorithmic trading platform (Python/Postgres/Kafka/Redis) and drove major DB performance wins (10x faster analytics; sub-10ms response consistency). Also shipped an end-to-end ML recruitment matching platform (scraping/ETL/modeling/Django deployment) with reported 92% matching accuracy, and emphasizes production reliability via monitoring, blue-green deploys, and robust workflow error handling.”
Mid-level Research Assistant specializing in interpretable ML and AI evaluation
Senior AI/ML Engineer specializing in NLP, LLMs, speech, and computer vision
Intern Data Science and Web Development student specializing in machine learning
Senior AI/ML Engineer specializing in NLP, LLMs, speech, and computer vision
Senior AI/ML Engineer specializing in NLP, LLMs, speech, and computer vision
Mid-level Machine Learning Engineer specializing in Generative AI and healthcare NLP
Manas Kumar Sherla
Junior Machine Learning Engineer specializing in NLP and LLM-based clinical AI
“Built a production automated resume matching system using Python, FAISS vector search, and Selenium-based job scraping, including mitigation for IP blocking and heterogeneous site structures. Also develops LLM/RAG applications with LangChain, using Pydantic-guardrailed structured outputs and LLM-as-a-judge evaluation (including a project focused on tone/semantics for a 3D avatar’s emotional responses).”
Junior Machine Learning Engineer specializing in Agentic RAG and Document AI
Entry AI Engineer specializing in machine learning, computer vision, and data mining