Vetted Kubernetes Professionals

“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.”

“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).”

“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.”

“Robotics software engineer (10+ years ROS/ROS 2) currently leading the perception stack for Omron’s AMR fleet, including a scalable factory SLAM system that combines vision with laser SLAM to handle corridor aliasing. Strong in real-time embedded optimization on NVIDIA Jetson (CUDA + profiling) and fleet-scale validation via multi-robot Isaac Sim scenarios (USD-to-ROS 2 bridging, Nav2 in crowded scenes). Also contributed to a cloud-native reality-capture/3D reconstruction pipeline at Hilti using Docker and Kubernetes.”