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Vetted Hugging Face Professionals
Pre-screened and vetted.
Mid-level Full-Stack Software Engineer specializing in distributed systems and GenAI platforms
Mid-level AI Solutions Architect & Product Leader specializing in enterprise GenAI systems
Vigynesh Bhatt
Mid-level Software Engineer specializing in backend, cloud, and ML systems
“Software engineer with experience across Goldman Sachs, BYU Broadcasting, Juniper Networks, and an edtech startup (Doubtnut), spanning data migrations, AWS-based media backends, and microservices observability. Built a Redis/ElastiCache caching layer in front of DynamoDB/S3 to improve media delivery latency and cost, and created an SEO indexing automation tool using the Google Search Console API that saved ~15–30 person-hours per day.”
Rajan Souda
Mid-level AI Engineer specializing in Generative AI and MLOps
“Built and deployed a production LLM-powered clinical support assistant at BJC HealthCare (RAG + transformer) to answer patient questions, summarize clinical notes, and support appointment workflows. Implemented PHI-safe data pipelines (Spark/Hadoop/Kafka) with automated scrubbing, dataset versioning, and audit logs, and runs the system on Docker/Kubernetes with Pinecone vector search while partnering closely with clinical operations staff.”
Tanmayee Chandanam
Mid-level Data Scientist specializing in recommender systems, NLP, and real-time ML pipelines
“AI/LLM engineer who built and productionized an internal RAG-based knowledge system that ingests diverse sources (PDFs, Markdown, Slack), scaled retrieval with distributed FAISS and parallel ingestion, and reduced hallucinations via re-ranking, grounding prompts, and post-generation validation. Also has hands-on orchestration experience with Airflow and Kubernetes for reliable ETL/model pipelines, monitoring, and staged rollouts; reports ~15% accuracy improvement and adoption as the primary internal knowledge tool.”
YAKKALI PAVAN
Mid-level Machine Learning & Generative AI Engineer specializing in NLP, CV, and RAG systems
“Built and deployed a production LLM-powered RAG document intelligence system used by non-technical enterprise stakeholders, cutting document search time by 40%+ while improving answer consistency. Demonstrates strong MLOps/data workflow orchestration (Airflow, AWS Step Functions, managed schedulers across GCP/Azure) and a metrics-driven approach to reliability, evaluation, and cost/latency optimization with guardrails and observability.”
Senior Machine Learning Engineer specializing in NLP, LLMs, and scalable ML platforms
Senior Applied Scientist specializing in LLMs, GenAI, and agentic systems
Director of Engineering specializing in capital markets risk, trading systems, and AI/ML platforms
Intern AI Product Manager specializing in enterprise AI security and agent platforms
Junior Full-Stack Software Engineer specializing in React, APIs, and Industrial IoT data platforms
Junior Software Engineer specializing in AWS cloud infrastructure and ML systems
Junior Software Engineer specializing in cloud backends, data engineering, and applied NLP
Executive AI & Data Product Leader specializing in Generative AI video and AdTech
Mid-level AI/Software Engineer specializing in NLP pipelines and LLM-driven automation
Mid-level Data Scientist specializing in GenAI, LLMs, and MLOps
Staff AI & Data Engineer specializing in LLM systems and real-time data platforms
Aaditya Voruganti
Junior AI & Software Engineer specializing in robotics and ML infrastructure
“Robotics engineer from UIUC’s Intelligent Motion Lab who led the perception stack for a humanoid robotic nurse, fusing camera/LiDAR/IMU on NVIDIA Jetson Orin for real-time localization and scene understanding across six robots. Deep expertise in ROS 2 and edge ML optimization (TensorRT, CUDA, zero-copy), delivering major latency/throughput gains (10 FPS to 22+ FPS) and building fault-tolerant pipelines with gRPC offloading and real-time reliability practices.”