Vetted Shell Scripting Professionals

“Embodied AI/robotics-focused ML engineer who built a real-time assistive Braille device by coupling transformer OCR with an Arduino-controlled electromechanical Braille cell, solving tight latency and hardware-integration constraints. Has recent work on geometry-grounded world models and a real-time 4D reconstruction foundation model (Any4D), and delivered measurable impact at Voxel AI by building a scalable headless simulation + synthetic data pipeline that improved a safety-critical algorithm’s recall by ~16%.”

“Embedded/robotics software engineer with Hyundai Motors experience who owned an AI-driven perception validation pipeline using a Transformer-based approach to generate stable synthetic in-cabin audio for autonomy/ASR testing, cutting downstream testing time by 50%+. Has hands-on ROS integration (IMU sensor streaming, inference, control nodes), MQTT-based distributed messaging, and cloud/container deployment experience (Docker, Node/Express, AWS, CI/CD).”

“QA professional with experience at Google and Meta, focused on end-to-end functional/regression testing, disciplined bug reporting (including ADB logs), and release readiness via staging build promotion and gating on critical/high-priority issues. Emphasizes PRD-driven test planning, edge-case coverage (e.g., low connectivity/low battery), and thorough verification across build versions.”

“Amazon Robotics engineer who deployed and scaled the Lumos camera-based package scanning work cell across EU sort centers (100+ work cells in 5+ sites), enabling remote launches via detailed runbooks and troubleshooting. Strong in AWS IoT/edge systems, with hands-on incident recovery (restored 34 down work cells) and secure multi-compute certificate provisioning using IoT Jobs, ACM/CA, and custom roles; delivered ~75% per-cell cost reduction vs Cognex-based approach.”

“Technology/architecture leader with Accenture experience delivering data- and AI/ML-driven products, including a legal contract search solution and customer sales analytics for AWS. Known for scaling distributed teams (onshore/offshore), making pragmatic architecture decisions, and solving hard data problems (proprietary sources, data quality) while implementing scalable integrations like Redshift-to-Salesforce via parallelized pipelines.”

“Backend/AI engineer who built a production GPU-backed real-time inference API at Nvidia and debugged burst-induced tail latency, cutting P95 by ~29% through dynamic batching and backpressure. Also shipped an end-to-end RAG + agentic operational diagnostics assistant with strict tool controls, evidence citation, confidence gating, and strong production guardrails, plus demonstrated hands-on Postgres optimization (900ms to 40–60ms).”