Vetted Docker Professionals

“Sole developer behind BirdieAI, an AI-powered golf booking platform built from the ground up, spanning frontend UX, backend services, AWS infrastructure, and Postgres database management. Worked directly with a cofounder in a startup setting to scope and ship an MVP, then improved production reliability significantly by reducing a key extraction failure from 1 in 15 to 1 in 300 while adding operational safeguards and user-driven product improvements.”

“Lead front-end engineer focused on large-scale React microfrontend enterprise platforms, with experience spanning telecom e-commerce and financial services. Stands out for combining architecture ownership with deep browser-level performance expertise, including a 42-45% route transition improvement and UX changes that cut workflow completion times by about 25% for demanding institutional users.”

“Robotics ML/software engineer focused on Vision-Language-Action control for 7-DoF robots, replacing tokenized action decoding with continuous regression heads (including a logit-weighted expectation approach) to improve stability and real-time behavior. Strong in ROS1/ROS2 systems integration and debugging closed-loop manipulation issues via latency instrumentation, QoS-aware distributed messaging, and sim-to-real validation using Gazebo/Unity, Docker, and CI pipelines.”

“At Esri, the candidate is building a production LLM-powered WebGIS AI framework that embeds an AI assistant into web maps and routes natural-language requests into ArcGIS JavaScript SDK functions via a LangGraph-orchestrated, multi-agent system. They emphasize production reliability and scale (strict tool calling/JSON, live schema validation, query guardrails) and rigorous evaluation/observability using LangSmith, offline prompt datasets, and latency/tool-call accuracy tracking.”

“Backend-focused engineer building customer support/order-tracking platforms with Java 17/Spring Boot microservices and a React/TypeScript frontend. Deep experience running event-driven systems on Kubernetes (Kafka, Redis, MySQL) with strong observability (Prometheus/Grafana/Splunk), SLOs, and safe deployment practices (feature flags, canaries). Also built an internal monitoring/debugging dashboard that consolidated metrics and logs for on-call engineers and was adopted by other teams to speed incident response.”

“Built and deployed a production RAG-based LLM Q&A and summarization platform for internal documents, emphasizing grounded answers with structured prompting and citations to reduce hallucinations. Experienced orchestrating end-to-end LLM workflows with LangChain plus cloud pipelines (Azure ML Pipelines, AWS), and runs iterative evaluation using both metrics (accuracy/hallucination/latency/cost) and real user feedback to drive reliability.”

“Robotics software engineer who has built full ROS 2 stacks for both a semi-automated robotic ultrasound system (UR5e + depth camera) and a quadrotor planning/MPC pipeline in Gazebo. Strong in integrating major ROS 2 frameworks (MoveIt/Nav2/RTAB-Map), writing custom packages (URDF, ACADOS-based MPC, laser landmark detection), and optimizing real-time behavior via GPU parallelization and distributed multi-threaded ROS 2 architectures; also contributes to ROS 2 core (structured parameters).”

“AI engineer building and deploying deep-learning-based optimization/control systems for petrochemical plants, with a focus on maintaining operational stability under real-world constraints. Core contributor to model and inference design; introduced a stability-focused non-linear objective and sped up second-layer optimization via on-the-fly first-order approximations. Experienced using Kubernetes for end-to-end testing and effective in translating customer expectations into measurable evaluation plots for non-technical stakeholders.”

“ML/LLM practitioner with experience at Truveta building an LLM-based evaluation framework; identified non-overlapping evaluator failure modes and proposed an ensemble approach that enabled scaling training data and drove ~5% performance gains across multiple internal projects. Strong focus on robustness to distribution shift (augmentation/domain adaptation/meta-learning) and production reliability via monitoring, drift detection, and safe fallbacks.”

“Cloud-focused DevOps/Infrastructure engineer with hands-on AWS high availability, migration cutovers, and production automation. Built Jenkins-based CI/CD pipelines (Git, SonarQube, Artifactory) and manages Terraform IaC with S3/DynamoDB remote state, PR-based reviews, and staged environment promotion; targets $160k base. No direct IBM Power/AIX/PowerHA experience.”

Akashleena Sarkar

Screened

Junior Software Engineer specializing in robotics and real-time distributed systems

Mountain View, CA2y exp

“Robotics software engineer focused on low-compute navigation/SLAM: built a 6-DOF SLAM validation pipeline (IMU + 2D LiDAR + ultrasonic) producing ~1cm OctoMap accuracy and deployed it on an Intel Atom by optimizing particle-filter SLAM with a greedy max-likelihood update. Deep ROS 2 experience (executors, composable/lifecycle nodes, QoS, timestamping) plus simulation and deployment tooling (Gazebo C++ plugins, Docker, CI/CD, ROS 2 build farm) and drone navigation work with MAVROS/PX4.”

Alp Komban

Screened

Junior Machine Learning Engineer specializing in computer vision for medical imaging

Mountain View, CA2y exp

“Applied ML/LLM practitioner working in healthcare-facing products, using RAG and LoRA fine-tuning on medical data and implementing production monitoring (confidence scoring) for clinician oversight. Has hands-on experience debugging agentic/LLM pipelines (including OCR preprocessing fixes) and regularly delivers technical demos to doctors, investors, and conferences—contributing to adoption and even helping close a funding round through end-to-end pipeline walkthroughs.”

“Built a production-grade agentic document intake system that converts PDFs into structured records with strict schema validation, confidence-based retries, and a human review UI. Demonstrates strong practical judgment around making LLM systems reliable in enterprise workflows, including custom orchestration, observability, and continuous evals rather than relying on off-the-shelf abstractions.”

Sarthak Chauhan

Screened

Junior Software Engineer specializing in AI-powered backend and full-stack systems

San Francisco Bay Area, CA2y exp

“Built production AI agents at HubSpot for sales teams, including Next Best Action, Deal Risks, and Deal Plans. Combines frontend React/TypeScript implementation with backend prompt engineering, evaluation in Braintrust, caching, and generation pipeline work, and has experience shipping fast with beta feedback and gated rollouts.”

“Full-stack/product-minded engineer with recent experience in both an early-stage AI startup and a B2B payments marketplace. Stands out for building a pgvector-based semantic cache that reduced LLM latency by 35% and for shipping audit-heavy payment infrastructure with Stripe/Plaid, idempotent webhook handling, and major reconciliation query optimizations.”

“Graduate robotics researcher (Georgia Tech/Georgia Tech Research Institute) who helped modernize the Georgia Tech Robotarium by migrating its comms stack from MQTT to ROS2 across MATLAB/Python and updating embedded Teensy firmware for new sensors. Currently validating ToF distance sensors and integrating IMUs, with planned GTSAM factor-graph SLAM sensor fusion; also debugged and improved a decentralized coverage-control algorithm at swarm scale (1000–2000 agents) using computational geometry and literature-backed methods.”

“Industrial AI/ML practitioner with experience deploying real-time monitoring and anomaly detection in a regulated Sanofi vaccine manufacturing facility, including root-cause workflows, logging/alerting, and SOP-aligned validation—achieving ~90% faster anomaly detection. Also built Python/NLP-style automation to accelerate instrumentation & control documentation (~40% faster) and delivered end-to-end predictive analytics for an agri-food operations/distribution client using close operator and leadership feedback loops.”

“Robotics software engineer who built the full control stack for a fleet of manufacturing/repair robots in Relativity Space R&D (perception, planning, motion control, integration, deployment). Has ROS/ROS 2 experience spanning custom SLAM (LiDAR+IMU), multi-robot coordination, and multi-drone control (Pixhawk 4, minimum-snap trajectories), with strong real-world debugging and simulation/CI testing practices (Gazebo, CI/CD, some Docker).”

“Backend/platform engineer who owned high-volume Java/Spring Boot microservices on AWS (Kafka + RDS/DynamoDB) and has hands-on experience debugging complex production latency incidents across DB, JVM/GC, and async consumers. Also shipped applied AI features for ops, including an LLM-powered log analysis assistant and an incident-response agent with strong safety guardrails (schema-validated tool use, retries/backoff, and human-in-the-loop escalation).”

“Backend/AI engineer at Intuit who built a production AI-powered case assistant for support agents (FastAPI on AWS EKS) combining Postgres case data, OpenSearch retrieval with embedding reranking, and internal LLMs. Improved peak-season reliability by diagnosing P95/P99 timeout spikes and cutting P95 latency from ~800ms to <400ms via composite indexing, keyset pagination, connection pool tuning, and caching, while adding grounded-generation guardrails (evidence packs, confidence thresholds, fallbacks, human-in-the-loop).”

“FinTech/AI engineer who has shipped an end-to-end discrepancy-detection product for financial managers using Next.js, FastAPI/GraphQL, Pinecone, and AWS (with dev/staging/prod, observability, A/B testing, and documentation). Also built an AI-native “AI Genesis” system with agentic cyclic workflows, routing, and tool use, and has experience modernizing legacy systems via the strangler fig pattern while coordinating with senior stakeholders on a 5G autonomous simulation platform.”

Ho-Wei Lu

Screened

Junior Robotics Engineer specializing in motion planning and control

Berkeley, USA1y exp

“Robotics software engineer who built a ROS2-based ping-pong ball interception system on a 7-DOF Sawyer arm, spanning real-time vision, trajectory prediction, and an MPC joint-velocity controller to hit a flying ball within ~1 second. Demonstrated strong real-time debugging and systems integration skills (timestamp-based latency analysis, event-based redesign, ROS2 QoS tuning) and is currently working with Isaac Sim in Docker with GitHub-based CI/CD for assembly-task simulation.”

Rahul Kushwaha

Screened

Mid-level Software Engineer specializing in FinTech and scalable microservices

Texas, USA5y exp

“Backend/platform engineer focused on high-traffic financial systems, owning real-time event-driven ingestion and Kafka streaming pipelines using Python/FastAPI, Avro schemas, and AWS services. Has hands-on Kubernetes (EKS) and GitOps/CI-CD experience (ArgoCD/Jenkins) and supported large-scale migrations from legacy VMs to containerized microservices with zero/low-downtime cutovers.”