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Vetted Kubernetes Professionals

Pre-screened and vetted.

MM

Entry Backend Software Engineer specializing in Python/FastAPI and cloud-native APIs

Milpitas, CA0y exp
California State University, ChicoCalifornia State University, Chico

Backend engineer who built and evolved a low-latency document search platform (C++/gRPC on Kubernetes with a vector database), emphasizing resilience under concurrent load through strict deadlines, retries, idempotency, and observability. Also experienced building secure, frontend-friendly FastAPI services (Pydantic + JWT) and executing safe incremental refactors using feature flags and parallel validation.

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MH

Minh Huynh

Screened

Junior AI/ML Engineer specializing in LLM systems and personalization

Anaheim, California2y exp
Reach BrandsCity University of Seattle

Backend engineer who built and scaled AmazonProAI, a multi-tenant SaaS platform for Amazon sellers, using a modular Django/DRF monolith with strict seller-level isolation and security controls. Led a controlled SQLite-to-PostgreSQL migration and hardened bulk Excel ingestion with idempotency and data integrity constraints to prevent duplicate metrics and noisy alerts while keeping the system ready for future service extraction.

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JM

Intern Software Engineer specializing in Java/Spring Boot and REST APIs

Lake Success, NY0y exp
LIJMCBrooklyn College (CUNY)
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SJ

Junior Full-Stack Data Engineer specializing in data pipelines and analytics

Pune, India1y exp
TSL ConsultingUniversity of the Pacific
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KR

Junior Full-Stack Software Engineer specializing in React/Next.js and TypeScript

Remote, NJ2y exp
The F Word IncBergen Community College
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SO

Junior Software/AI Engineer specializing in GPU-accelerated HPC and machine learning

Wichita Falls, Texas4y exp
Midwestern State UniversityMidwestern State University
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KN

Entry-Level Full-Stack Software Engineer specializing in backend systems and cloud deployment

Long Beach, CA0y exp
BeachHacks, CSULBCal State Long Beach
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RR

Rutvi Rathod

Screened

Junior Full-Stack Software Engineer specializing in AI and web applications

San Jose, CA1y exp
FreelanceChhotubhai Gopalbhai Patel Institute of Technology

LLM/AI backend engineer with hands-on experience taking customer LLM prototypes into production using FastAPI, containerization, CI/CD, and OpenTelemetry-based observability. Demonstrated measurable impact by cutting LLM costs ~40% and reducing workflow errors ~50% through schema-enforced outputs, better tool definitions, retries, and prompt/model optimization; also supports pre-sales via technical discovery and rapid integration demos.

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KM

Kumar Manik

Screened

Intern AI Engineer specializing in LLMs, MLOps, and RAG systems

0y exp
Elevate LabsBarkatullah University

Built and shipped a production-grade RAG-powered news summarization and Q&A product, tackling real-world issues like retrieval drift, hallucinations, latency, and autoscaling deployment (Docker + FastAPI + Streamlit Cloud). Experienced in end-to-end ML/LLM workflow automation using Airflow, Kubeflow Pipelines, and MLflow, and has demonstrated business impact (40% inference precision improvement) through close collaboration with non-technical stakeholders at Evoastra Ventures.

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VA

Vivek Agarwal

Screened

Robotics software engineer who built a full autonomous navigation pipeline on TurtleBot3 in ROS2 from bring-up and SLAM through custom A* planning, obstacle avoidance, and frontier exploration—without relying on Nav2. Demonstrated strong debugging and performance optimization (QoS fix with AMCL; reduced exploration mapping time from ~12 to <7 minutes) and brings 2+ years of HPE cloud/edge deployment experience with Docker/Kubernetes/Helm and GitHub Actions.

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AC

Built and deployed an LLM-powered financial document processing and summarization platform at Morgan Stanley using a production RAG pipeline (PDF ingestion, embedding-based retrieval, schema-constrained JSON outputs) delivered via FastAPI microservices on Kubernetes. Drove measurable impact (40% reduction in manual review time) and improved factual accuracy for numeric fields by 30% through metadata-aware retrieval, strict schemas, and post-generation validation, with a human feedback loop from financial analysts.

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Robotics-focused software engineer/technical lead with Google/Android engineering experience, building automation and robotic framework architecture in C++/Python. Has hands-on experience with ROS/ROS2, SLAM/localization/mapping, motion planning, and scaling distributed robotics nodes using Docker/Kubernetes with CI/CD (Jenkins), plus REST API-based integration testing and validation.

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JR

Senior Backend Engineer specializing in microservices and event-driven systems

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