Vetted Docker Professionals

“Robotics software engineer with UC Irvine capstone experience building an autonomous rover end-to-end: ROS 2 navigation (slam_toolbox + Nav2) on Jetson Xavier, depth point-cloud integration for obstacle avoidance, and an on-device speech-to-action interface that converts natural language into Nav2 goals. Also has prior full-time experience integrating a safety assurance decision engine into distributed autonomous drones over secured mesh networks, emphasizing reliable communication under real-world network constraints.”

“Robotics software engineer who owned the end-to-end navigation stack for a mobile manipulation robot (Cone-E), integrating ZED-2i SLAM into a real-time occupancy grid with live obstacle avoidance, A* planning, and lookahead control. Strong in real-time debugging and stability improvements (goal snapping/locking, obstacle persistence, rate-limited replanning) and validates changes on hardware, supported by simulation (Gazebo/Webots) and Docker/CI-based testing.”

“LLM/RAG practitioner who productionized an LLM-driven customer communication and transaction understanding system at PayPal, emphasizing privacy/compliance guardrails and large-scale data normalization. Experienced in real-time debugging of hallucinations via retrieval pipeline tuning and in leading hands-on developer workshops and sales-aligned POCs to drive adoption.”

“Firmware architect/lead engineer for automotive LiDAR sensors, designing RTOS-based, layered firmware and solving high-throughput real-time constraints using DMA and lock-free buffering. Built ROS nodes to bridge embedded sensor output to higher-level perception (point clouds, diagnostics, configuration) while isolating real-time logic in firmware. Established an end-to-end CI/CD pipeline with GTest unit tests plus SIL/HIL automation and Dockerized build/test environments.”

“Software engineer with strong end-to-end ownership of search and listing systems (React/TypeScript frontend with Node.js + Spring Boot backends), focused on shipping fast while managing risk via feature flags, testing, and metrics. Demonstrated measurable UX/performance wins (reduced latency and search abandonment) and built internal observability tooling (dashboard + alerts) that improved incident response. Experienced with microservices reliability patterns including idempotency and dead-letter queues.”

“Frontend-focused engineer operating at a staff level with experience at Amazon and startups, known for rescuing high-impact, frontend-heavy systems through architecture, performance, and quality improvements. Delivered outsized results including cutting load times from ~90s to ~3s, raising test coverage from <1% to >80%, and enabling multi-team adoption of modern state management via training sessions for 50+ engineers.”

“Senior frontend engineer with experience leading high-impact React/TypeScript products at HelloFresh and CAA, including an A/B-tested onboarding flow shipped across multiple international brands. Modernized a legacy .NET frontend to Next.js using SSR and performance techniques (caching/memoization/lazy loading) and implemented robust testing/monitoring (Cypress, Honeycomb, GA) in fast-paced, production-deploy environments.”

“Robotics software engineer with hands-on ROS2 autonomy experience across F1TENTH and Turtlebot platforms, building planning/control behaviors (Pure Pursuit, Follow-the-Gap, emergency braking, PID wall following) and validating in Gazebo/RViz. Also integrated a custom curvature-based speed planning node into Autoware (with AWSIM), demonstrating practical autonomy stack integration and strong debugging of LiDAR pipelines.”

“Software engineer with Capital One experience contributing to shared internal “open-source style” JavaScript/React/TypeScript libraries (component library and hooks/utilities). Drove measurable performance gains (~25% improvement) by refactoring hooks to prevent unnecessary re-renders, and improved adoption via stronger documentation, testing (Jest), semver discipline, and code review/PR workflows; also stabilized a backend service by adding monitoring and automated tests in an unstructured project.”

“Built a production internal RAG-based Q&A assistant at Huawei for ~4,000 engineers over a 12M-document Elasticsearch corpus, replacing link-only search with synthesized answers and achieving 87% user acceptance while keeping hallucinations under 0.4%. Pairs rigorous offline benchmarking (RAGAS, PR-gated F1 improvements) with human A/B testing and OpenTelemetry-based production monitoring, and also has strong Kubernetes/SRE experience orchestrating 50+ gRPC services with major MTTR and pager-fatigue reductions.”

“Computer-vision-focused candidate with internship experience at ASML (Silicon Valley) building object detection models (YOLO, RT-DETR) for SEM defect inspection. Worked end-to-end on preparing multi-resolution datasets and tuning/training strategies, noting improved performance on low-quality images when training jointly on higher-resolution data.”

“Development manager focused on developer productivity and platform enablement in a polyglot microservices environment. Drove ~50% productivity gains by evaluating and rolling out AI coding copilots with team training and cross-team demos, and designed a Disaster Recovery framework adopted by 50+ microservice teams. Also led edge-focused Python runtime optimization and relies on heavy test automation to safely execute large refactors during major platform upgrades.”

“Backend engineer focused on building production-ready Python services (Flask/FastAPI) with strong performance and scalability instincts—Celery/Redis background processing, robust multi-tenant isolation (Postgres RLS), and pragmatic CI/Docker operations. Demonstrated measurable DB optimization impact (cut a critical analytics query from ~1–2s to ~100–150ms) and has hands-on experience integrating LLM/ML workflows (OpenAI, LangChain, embeddings, Redis/FAISS vector stores) without degrading API responsiveness.”

“Built a production AI-driven QA automation platform using a multi-agent architecture (MCPs + LangGraph) to run parallel website tests across multiple device environments via automated image building and containerization. Currently collaborating with restaurant operators and managers to deliver an agentic restaurant analytics system, emphasizing deep domain discovery with non-technical stakeholders.”

“ML/NLP engineer with experience at Flatiron Health building a production NLP platform that processed millions of clinical notes, using BERT/BiLSTM-CRF and spaCy to extract and normalize entities from noisy EMR text with oncologist-in-the-loop validation. Also built scalable retail ML workflows (Spark + Kubernetes + feature store caching) and applied vector databases plus contrastive-learning fine-tuning to improve retrieval relevance and recommendations.”

“Backend/DevOps-focused engineer with healthcare and financial systems experience, including an ICU readmission risk platform delivering real-time ML scores via a secure FastAPI service (PyTorch model serving, PostgreSQL, Celery/Redis) deployed on AWS with strong observability. Has hands-on Kubernetes GitOps delivery (Helm, ArgoCD, HPA) and has supported a JPMC on-prem-to-AWS microservices migration using phased validation and blue-green cutovers, plus Kafka/Avro streaming for real-time transaction processing.”

“Backend/automation engineer who led the design of an OOP Python test automation framework for AWS infrastructure (Behave + Jenkins), cutting regression effort from weeks to a 3–4 hour run. Has hands-on cloud and DevOps experience across AWS (boto3, ECS, AMI automation via GitHub Actions) plus data/migration work including on-prem-to-cloud Oracle Retail DB migration with rollback planning and a Kafka + ML fraud-detection streaming pipeline.”

“Completed an Amazon externship building a GPT-4 + RAG pipeline to summarize themes from hundreds of employee reviews for workforce analytics aimed at improving warehouse retention. Emphasizes production-readiness through labeled-data evaluation, source attribution for explainability, human-in-the-loop review, and rigorous data cleaning/observability to debug real-world LLM workflow issues.”

“Full-stack engineer with strong DevOps/AWS production experience who builds and operates multi-agent AI systems end-to-end (Streamlit/Python through Docker/Kubernetes and ECS/Fargate). Has delivered measurable outcomes: sub-2s latency and ~92% routing accuracy for an AI wellness assistant, shipped an AI-for-BI prototype in under 6 weeks cutting analysis time ~40%, and improved pipeline iteration speed ~35% via modularization and CI/regression checks.”

“Head of Robotics at Orbital Composites who built the full ROS-based software stack ("OrbOS") for multi-robot KUKA-arm 3D printing of carbon-fiber composite geometries. Deep in motion planning and real-time control—created a pipeline to turn underconstrained toolpaths into optimal joint trajectories at massive command scale, plus redundant safety gatekeeping and a 250Hz synchronized robot+extruder controller. Has operated in a technical-founder capacity for ~6 years and values an engineering culture of openness, honesty, accountability, and high ownership.”

“Engineering manager leading a 15-person team at FBN on the Gridbull platform, shipping a self-serve pricing/quoting tool for structured commodity products using real-time futures market data. Owns architecture and reliability for third-party data integrations (WebSocket + REST fallback), including resolving a day-one production incident caused by undocumented vendor connection resets. Introduced lightweight Technical Implementation Plans to improve cross-functional alignment and delivery speed in a high-growth environment.”

“CTO who ties technology strategy directly to business outcomes, building multi-year roadmaps with measurable ROI. Led major modernization (cloud, data platform, unified API, microservices + CI/CD) delivering 5x faster releases/deployments, 99.8% uptime, and 40% user growth without headcount increases, while scaling engineering from 15 to 80+ in ~18 months.”

“Software engineer with hands-on experience building a distributed ticketing system on AWS (Terraform, Go, MySQL) focused on high-concurrency reliability (locks/queues to prevent duplicate ticket confirmations) and load-tested performance. Also independently owned and shipped an Airflow automation script to stop/restart workflows during deployments with email notifications, reducing manual operational effort.”

“Full-stack engineer with fintech/trading domain experience (Fidelity) and startup SaaS CRM/billing platform work (Zoho), building real-time portfolio analytics and trade-processing systems. Strong in microservices, event-driven architectures (Kafka/WebSockets), and AWS/Kubernetes operations with measurable performance gains (~34–35% latency reduction) and maintainability improvements (~40% faster deployments). Targeting a founding full-stack engineer role in NYC with meaningful equity.”