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Vetted scikit-learn Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in LLMs and RAG systems
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
Mid-level Python Backend Engineer specializing in microservices and AWS
Junior Software Engineer specializing in AI/ML, data pipelines, and real-time dashboards
Mid-level AI Engineer specializing in LLMs, RAG, and enterprise compliance & fraud systems
Junior Full-Stack Software Engineer specializing in cloud-native microservices and data pipelines
Senior AI/ML Engineer specializing in NLP, LLMs, speech, and computer vision
Senior AI Engineer specializing in LLMs, agentic systems, and ML infrastructure
Mid-level Machine Learning Engineer specializing in Generative AI and healthcare NLP
Intern Full-Stack Software Engineer specializing in AI-powered applications
Maulik Maganbhai Ghatala
Entry Backend Software Engineer specializing in Python/FastAPI and cloud-native APIs
“Backend engineer who built and evolved a low-latency document search platform (C++/gRPC on Kubernetes with a vector database), emphasizing resilience under concurrent load through strict deadlines, retries, idempotency, and observability. Also experienced building secure, frontend-friendly FastAPI services (Pydantic + JWT) and executing safe incremental refactors using feature flags and parallel validation.”
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).”
“Built a production LLM-powered interview-prep app that ingests job postings and generates tailored preparation plans. Iterated from a single generalist LLM to a multi-LLM pipeline and used RAG to ground the final chat assistant on locally stored intermediate outputs; has also experimented with n8n vs Python-coded pipelines for orchestration.”
Mid-Level Full-Stack Developer specializing in Python/FastAPI and React
Junior Software/AI Engineer specializing in GPU-accelerated HPC and machine learning