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Vetted C Professionals

Pre-screened and vetted.

SP

Senior Software Engineer specializing in AI/ML and cloud backend systems

Santa Clara, CA5y exp
Machine Learning and Safety Analytics LabSanta Clara University
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RT

Junior AI/ML Engineer specializing in LLM applications, RAG, and multimodal computer vision

Milpitas, CA3y exp
PicaggoKansas State University
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SC

Intern Software Engineer specializing in AI-driven web applications

United States2y exp
Limelight Logic IncUniversity of North Texas
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SP

Mid-level Software Engineer specializing in high-performance systems and hardware validation

Buffalo, NY5y exp
CytocyberneticsUniversity at Buffalo
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HV

Mid-level Data Scientist specializing in FinTech and healthcare NLP/LLMs

4y exp
University of North TexasUniversity of North Texas
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TT

Mid-Level Software Engineer specializing in AI/ML, cloud deployment, and full-stack systems

Boston, Massachusetts6y exp
West Virginia State University R&D CorporationWest Virginia State University
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SZ

Junior Financial Data Analytics and Programming Candidate

Babson College
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QQ

Entry-Level Full-Stack Software Engineer specializing in AI-driven web applications

Plano, TX
Yangzhou University
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BN

Senior VR/AR Software Engineer specializing in graphics, OpenXR, and computer vision

Tbilisi, Georgia9y exp
Atopia Space
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IS

Senior Unity/C# Developer specializing in performance, rendering, and VR

Gdansk, Poland7y exp
Guli Games
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TB

Tony Barreto

Screened ReferencesModerate rec.

Mid-Level Full-Stack Software Developer specializing in modern web apps

San Francisco, CA5y exp
DRIMOVCity College of San Francisco

Product-focused full-stack builder who has shipped and operated multiple production apps from scratch, including an e-commerce bakery delivery scheduler (with concurrency controls and timezone handling) and a real-time passenger music-request system for Lyft rides that hit and resolved YouTube API rate-limit scaling issues via debouncing and caching. Strong in React+TypeScript and Node.js/TypeScript backends, with solid PostgreSQL/PostGIS data modeling and performance tuning.

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RP

Rukmini Pisipati

Screened ReferencesModerate rec.

Junior AI/ML Engineer specializing in LLM automation and NLP

Indiana, United States2y exp
Human.ReadableUniversity of Cincinnati

Built and shipped a production LLM hallucination detection and monitoring pipeline using semantic-level entropy (embedding-clustered multi-generation variance) to flag unreliable outputs in downstream automation. Implemented a scalable async architecture (FastAPI + Docker + Redis/Celery) with strong observability (structured logs + PostgreSQL) and developed evaluation loops combining controlled prompts and human review; also partnered with non-technical stakeholders on AI-driven form validation/document processing.

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DS

Dhairya Shah

Screened

Entry-level Machine Learning Engineer specializing in computer vision and systems

Buffalo, NY1y exp
University at BuffaloUniversity at Buffalo

ML-focused builder who has shipped an end-to-end income-class prediction product: built the data pipeline, trained models, deployed via Streamlit with a live UI, and tracked success via accuracy (84%), adoption, and latency. Demonstrates strong practical MLOps instincts (Docker/Streamlit Cloud, logging/monitoring, caching) and data engineering reliability patterns (schema checks, idempotency, retries, backfills) while iterating quickly in ambiguous, solo-project environments.

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DP

David Pang

Screened

Intern Full-Stack Software Engineer specializing in web apps and healthcare APIs

1y exp
ScriptChain HealthUniversity at Buffalo

Full-stack developer who built an end-to-end e-commerce application with admin/blog/announcement features using Node/Express and AWS S3, emphasizing security via expiring presigned URLs. Also has strong distributed-systems fundamentals from implementing the Raft consensus algorithm (replication logs, majority acks, leader elections) and has created build automation tools (GNU Makefiles/scripts) to streamline team workflows.

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CK

Entry-Level AI Engineer specializing in NLP and LLM-powered applications

Fairfax, VA1y exp
George Mason UniversityGeorge Mason University

AI engineer who built an agentic, production-deployed LLM workflow for tobacco violation parsing and automated multi-case creation, using six specialized agents and a human-in-the-loop confidence-threshold routing design. Addressed data privacy constraints by generating synthetic datasets with LLM prompting, and orchestrated reproducible end-to-end pipelines in LangChain with robust testing and evaluation (precision/recall, micro-F1).

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TS

Tirth Shah

Screened

Mid-level AI/ML Engineer specializing in anomaly detection, data tooling, and cloud-native systems

Chico, CA4y exp
Chico State EnterprisesCalifornia State University, Chico

Backend/platform engineer who built an LLM-driven QA automation system (“mockmouse”) using a Flask orchestration microservice, Socket.IO real-time updates, Redis caching, and strict Pydantic schemas to turn prompts into reliable action graphs and automated browser tests. Has hands-on Kubernetes delivery experience (Docker/Helm/Jenkins) and has supported large migration programs, validating ETL cutovers with 1M+ synthetic records and rigorous output comparisons; also built event-driven monitoring/anomaly detection streaming into Grafana.

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SB

Samuel Braude

Screened

Junior Computer Science student specializing in robotics, ML, and quantum computing research

San Diego, CA2y exp
San Diego State UniversitySan Diego State University

Hands-on engineer who has taken an LSTM Bitcoin forecasting model from notebook to a production-grade, monitored API (Docker/Gunicorn/Nginx, Prometheus/Grafana, blue-green rollback) delivering 99.9% availability and ~110–120ms p95 latency. Also built an RFID self-checkout prototype spanning Raspberry Pi + firmware + networking, using deep instrumentation to eliminate double-charges/timeouts (<0.1%) and reduce checkout time ~20% through idempotency, debounce logic, and hardware fixes.

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JS

Jatin Soni

Screened

Mid-level Software Engineer specializing in Generative AI and scalable backend systems

Corona, CA3y exp
WellomyTechCalifornia State University, Los Angeles

Backend/AI engineer with production experience in legal tech: built a high-scale licensing/subscription API (FastAPI/Postgres/Stripe) and shipped a RAG-based chatbot for an eDiscovery platform. Designed a robust legal document ingestion workflow that processes thousands of documents into a searchable vector index with clear retry/escalation logic, and has demonstrated measurable Postgres performance wins (200ms to 10ms) using EXPLAIN ANALYZE and composite indexing.

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JM

Junior Software Engineer specializing in automation and full-stack development

Upland, CA2y exp
Alpine AutomotiveCalifornia State University, Monterey Bay

Backend-focused engineer who built a time-sensitive data retrieval system for a source with no public API, using an AWS EC2-hosted persistent browser session plus a PostgreSQL TTL caching layer—cutting manual retrieval by 99% and achieving sub-10-second average retrieval. Emphasizes production security (Secrets Manager, encryption, IP allowlisting, rate limiting) and robustness via testing and edge-case handling (atomic file operations).

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SS

Entry-Level Software Engineer specializing in AI, systems programming, and full-stack development

San Jose, CA1y exp
San José State UniversitySan José State University

Systems-focused C++ engineer who built a 32-bit CPU simulator end-to-end (custom ISA, full memory model, fetch-decode-execute loop) and solved tricky recursion/stack-frame correctness issues through heavy instrumentation and tracing. Has strong Linux and user-kernel boundary experience (procfs) plus modern build/test tooling (Docker, CI/CD, pytest), and is confident ramping quickly into ROS/ROS2 despite not having used it directly.

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AA

Mid-level XR Developer specializing in Unity VR/MR training simulations

Benguerir, Morocco5y exp
IDC Morocco1337 Khouribga

XR/VR Unity developer who has shipped to Meta Quest and led industrial VR projects. Built a Meta Quest 3 scaffolding safety training simulation using the XR Interaction framework, emphasizing instructional UX (cognitive load reduction) with interactive audio guidance, and has hands-on experience debugging device-only URP rendering issues (e.g., anti-aliasing conflicts causing ghosting/distortion).

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