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Vetted Hugging Face Transformers Professionals
Pre-screened and vetted.
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level AI/ML Engineer specializing in MLOps, real-time ML, and LLM/RAG systems
Intern AI Researcher specializing in NLP, multimodal generative AI, and medical imaging
Junior AI Engineer specializing in LLM agents and RAG for energy operations
Mid-level Machine Learning Engineer specializing in fraud prevention and LLM systems
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Senior AI/ML Engineer specializing in Computer Vision, NLP, and Generative AI
Mid-level Software Engineer specializing in data platforms and full-stack systems
Principal Data Scientist specializing in Generative AI and MLOps
Mid-level AI/ML Engineer specializing in LLM evaluation, RAG, and GPU-accelerated inference
Intern Machine Learning Engineer specializing in RL post-training for LLMs and VLMs
Senior Software Engineer specializing in Python, AI/ML, and AWS cloud-native systems
Mid-level AI/ML Engineer specializing in NLP, transformers, and RAG systems
Mid-level AI/ML Engineer specializing in LLMs, RAG, and enterprise AI
Intern AI Software Engineer specializing in LLM inference optimization and model compression
Senior AI Infrastructure & Backend Engineer specializing in LLM systems
Senior AI Infrastructure Engineer specializing in LLM systems and real-time ML platforms
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.”
Surya Singh
Mid-level AI/ML Engineer specializing in FinTech and fraud detection
“ML/backend engineer with PayPal experience building high-stakes production systems, including a GenAI internal support assistant and a real-time fraud scoring pipeline. Strong in Python/FastAPI, model-serving infrastructure, RAG architecture, and production observability, with clear readiness to transition those backend patterns into a TypeScript stack.”
Sharath Nyalakonda
Mid-level AI/ML Engineer specializing in NLP, graph models, and MLOps for FinTech and Healthcare
“AI/ML engineer who has deployed production LLM/transformer-based systems for merchant intelligence and fraud/support optimization, delivering +27% merchant engagement and +18% payment success. Deep experience in privacy-preserving, PCI DSS-compliant data/ML pipelines (Airflow, AWS Glue, Spark, Delta Lake) and scalable microservices on Kubernetes, plus proven cross-functional delivery in healthcare claims analytics at UnitedHealth Group (12% HEDIS claim reduction).”
Sriram Rajaraman
Senior Infrastructure Platform Architect specializing in Kubernetes and hybrid cloud
“Platform/infra engineer with strong ownership of Kubernetes on VMware and day-to-day hybrid on-prem-to-AWS operations. Has hands-on experience automating infrastructure delivery with Terraform/Ansible/CI-CD, and has resolved real production issues spanning CSI storage reattachment during upgrades, vSphere storage-latency performance degradation, and hybrid connectivity/routing failures with improved validation, monitoring, and failover.”
Gagan Mundada
Intern Machine Learning Engineer specializing in multimodal AI and evaluation benchmarks
“ML-focused candidate with beginner ROS/ROS2 experience (custom pub-sub nodes; TurtleBot3 SLAM simulation debugging via topic inspection and transform/orientation checks). Has research/project exposure to LLM training approaches (GRPO with pseudo-labels using Hugging Face TRL on Qwen/Llama) and uses Docker/Kubernetes + CI/CD to run ViT saliency-attention/compression workloads on UCSD Nautilus infrastructure.”