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Vetted Hugging Face Professionals
Pre-screened and vetted.
Junior AI Engineer specializing in LLM agents and RAG for energy operations
Mid-level Data Scientist specializing in NLP, deep learning, and big data analytics
Senior Machine Learning Engineer specializing in GenAI, NLP, and MLOps
Mid-level AI & ML Engineer specializing in NLP, LLMs, and scalable ML systems
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
Mid-level Full-Stack Python Developer specializing in cloud-native FinTech and GenAI
Junior AI/ML Engineer specializing in LLMs, RAG, and document intelligence
Senior Data/GenAI Engineer specializing in cloud-native ML, RAG, and real-time data platforms
Mid AI/ML Engineer specializing in LLM systems and inference optimization
Executive engineering leader specializing in SaaS platform transformation and AI
Justin Turner
Executive Technology Leader (CTO/CIO/CISO) specializing in cloud, security, and data platforms
“CTO-level technology leader with experience building end-to-end tech strategy and roadmaps, modernizing legacy environments in healthcare (GenesisCare), and scaling engineering into large global teams (Amadeus). Built a DevOps organization at Syniverse for the Visibility Suite, implementing Kubernetes/Terraform/Chef automation that drove ~75% faster deployments, and is known for staying hands-on (including data center work) while leading strategically.”
Pujan Thapa
Mid-level AI Engineer specializing in LLM applications and enterprise automation
“Engineer with a notably mature AI-native development process: uses Claude/Claude Code in a test-first, iterative workflow and has led multi-agent builds across frontend, backend, and testing. Most notably, they led development of an AI voice agent platform, creating custom agent skills and enforcing clear architectural boundaries to deliver a stable, scalable system.”
Alexander Smith
Junior Software Engineer and Data Scientist specializing in AI/ML systems
“Built production-grade automation and ML/data pipelines at Dun & Bradstreet and ThreadNotion, spanning large-scale document classification, country risk report automation, and resilient Playwright testing for dynamic AI chat workflows. Particularly strong in turning brittle or ambiguous systems into reliable, observable, end-to-end automated platforms.”
Tara Munjuluri
Junior Software Engineer specializing in full-stack and AI systems
“Backend-focused engineer with end-to-end ownership experience on internal platforms at John Deere, including a workforce and skills system that cut manual review time by 40%. Brings a strong reliability and compliance mindset across Java/Python microservices, AWS infrastructure, and production operations, and has also built an LLM-powered RAG system over 1M+ records with emphasis on grounded outputs and observability.”
Zahan Goel
Junior AI/ML Engineer specializing in LLM systems and mechanistic interpretability
“Second most active contributor at Daice Labs, owning a production AI-powered software development collaboration platform’s end-to-end execution infrastructure (TypeScript/Next.js backend, Node.js CLI, shared libs). Built the full multi-agent pipeline (planning/codegen/summary), Supabase-backed context assembly and realtime state, Git/GitHub automation, and a provider-agnostic LLM abstraction with strict Zod validation and retries, backed by extensive tests and design specs.”
Darsh Sharma
Mid-level Software Engineer specializing in ML systems and microservices
“Teradata Text Security intern who built a production LLM-powered planner agent that decomposes complex tasks into dependency-aware subtasks (DAG/topological graph) and executes them via a custom orchestrator with parallelism, status tracking, and error handling. Also contributed to an HR-facing internal document chatbot concept to streamline onboarding, showing cross-functional collaboration.”
Pranav Rambhia
Junior Embedded Controls Engineer specializing in robotics and reinforcement learning
“Robotics/ML engineer with hands-on experience building multimodal waypoint prediction for autonomous driving using CLIP + LidarCLIP embeddings and PyTorch, including nuScenes data pipelines and baseline modeling. Also built ROS 2 nodes for TurtleBot maze navigation with an image-classification pipeline, and has Caterpillar experience doing dSPACE HIL testing with MATLAB/Simulink plant models for engine software validation.”
Pranav Puranik
Senior AI Engineer specializing in LLMs, RAG, and multimodal NLP
“Built a production LLM/RAG assistant for insurance/health claims agents that ingests 100–200 page patient PDFs via OCR (migrated from local Tesseract to Azure Document Intelligence) and delivers grounded claim detail retrieval plus summaries with PII/PHI guardrails. Experienced orchestrating large workflows with Celery worker pipelines and AWS Step Functions (S3-triggered, Fargate-based batch inference/accuracy aggregation), and collaborates closely with non-technical SMEs (claims agents/nurses) through shadowing, iterative demos, and SME-defined evaluation.”