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Vetted Natural Language Processing Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in LLM evaluation, RAG, and GPU-accelerated inference
Junior AI/ML Engineer specializing in NLP, LLM evaluation, and Azure MLOps
Mid-level Full-Stack Software Engineer specializing in AI-driven web applications
Mid-level Data Engineer specializing in ML, LLM pipelines, and analytics platforms
Mid-level AI/ML Data Engineer specializing in data pipelines, MLOps, and LLM/RAG systems
Senior Full-Stack Software Engineer specializing in SaaS, cloud, and AI/LLM applications
Junior Software Engineer specializing in cloud platforms, microservices, and AI/ML
Mid-level Machine Learning Engineer specializing in MLOps and scalable ML pipelines
Junior AI/ML Engineer specializing in LLMs, RAG, and document intelligence
Mid-level AI/ML Engineer specializing in NLP, transformers, and RAG systems
Mid-level Python Backend Developer specializing in FinTech and ML-driven fraud detection
Mid-level Full-Stack Software Engineer specializing in AWS microservices and web platforms
Mid-Level Full-Stack Python Engineer specializing in AI-powered web apps and cloud-native systems
Junior Robotics & AI Engineer specializing in autonomous systems and machine learning
Mid-level Software Development Engineer specializing in backend systems and ML platforms
Mid-level AI/ML Engineer specializing in recommendation, retrieval, and MLOps
Mid-Level Software Development Engineer specializing in AWS edge AI and generative AI apps
Peeyush Dyavarashetty
Intern AI/ML Engineer specializing in GenAI, LLMs, and agentic RAG systems
“AI/LLM practitioner who built a GPT-2-like language model from scratch at the University of Maryland using PyTorch and multi-GPU distributed training, with experiment tracking in Weights & Biases. As an AI Operations intern at ScaleUp360, delivered multiple production-style AI agent automations (Gmail classification and Fireflies-to-Claude workflows that extract and assign CEO tasks) and set up measurable evaluation using test cases and classification metrics.”
Pavan Devulapalle
Mid-level Software Engineer specializing in cloud platforms and AI-integrated full-stack development
“Backend engineer who built Flask-based internal APIs supporting GenAI-driven provisioning/diagnostics (Outpost/AWS Outposts-like environment), with deep hands-on optimization across Postgres/SQLAlchemy (2s to <200ms endpoint improvement). Experienced integrating ML/LLM workflows via AWS SageMaker and Bedrock, and designing multi-tenant isolation plus high-throughput Redis-backed background task pipelines (minutes to seconds).”