Vetted Cybersecurity Professionals

Dhairya Shah

Screened

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

Buffalo, NY1y exp

“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.”

Vinayak Jain

Screened

Junior AI Platform Engineer specializing in ML and cybersecurity

Melbourne, Florida1y exp

“Cybersecurity-focused candidate whose master’s thesis performed an empirical, systematic study of memory and disk forensics behavior across Windows and Linux under Trojan and ransomware conditions. Has experience optimizing and debugging large, real-time data-processing pipelines (e.g., memory dumps/logs) and using Docker for forensic analysis workflows; no robotics/ROS experience to date.”

“Full-stack system analyst/programmer at PeakPlay Sports (startup) who built an AI "coach" product end-to-end in ~2 months, using a LangGraph-orchestrated multi-agent architecture with a FastAPI backend. Shipped production RAG grounded in athlete history (OpenAI embeddings + vector store) with guardrails and a structured eval loop (golden set + LLM-judge + human review) to improve engagement and reduce hallucinations.”

“Built end-to-end product features for a Web3 monetization platform and also shipped a privacy-first mobile accessibility app, SenScribe, using on-device sound classification and LLM summarization with zero cloud dependency. Particularly interesting for roles spanning full-stack product engineering, mobile AI, and applied ML where careful debugging, stakeholder alignment, and real-world usability matter.”

“Unity VR developer who built "instructor tools" for a skydiving/canopy training simulator, including comfort-focused wind/landing assessment features to reduce motion sickness. Implemented the simulator’s full Photon PUN networking and added Agora-based video streaming so instructors could run sessions with participants joining from browsers/tablets, while managing real-world latency constraints.”

Uvesh Chauhan

Screened ReferencesStrong rec.

Mid-level Full-Stack Developer specializing in AI and cybersecurity platforms

New Delhi, India6y exp

“Builder of multiple AI products including Nova-Core, a multi-model assistant using Grok and Gemini, and Lumina Shield, a prototype for vulnerability detection and performance analysis that routes findings into Nova-Core for explanation and fixes. Also created a desktop voice agent ('Soul') and brings 6 years of experience in a non-profit audio consultancy, with a personal story of being a cancer survivor motivated by purpose-driven work.”

“Unity/VR developer who shipped and published "Avatar Academy," a VR training software platform, to the Meta Quest Store. Worked on a small team where they owned most of the Unity implementation while teammates handled visuals and the backend/database/web dashboard.”

Hilal Alhamdi

Screened

Junior IT Support & Web Developer with networking and data validation experience

Semarang, Central Java, Indonesia2y exp

“QA tester with hands-on experience across web, PC, and mobile (functional/usability plus compatibility, stability, and performance testing) looking to transition into console game testing. Familiar with the intent and coverage areas of Sony TRC/Microsoft XR/Nintendo LOT requirements and uses Jira/Trello plus AI-assisted workflows to speed up bug triage, documentation, and pattern detection.”

Daniel Manalu

Screened

Junior QA Tester specializing in banking and e-commerce applications

Surabaya, Indonesia1y exp

“Background in banking and e-commerce applications, positioning as an adaptable learner pivoting toward console game QA. Proactively self-studying platform certification requirements (Sony TRCs, Microsoft XR, Nintendo LOT) and uses AI tools (ChatGPT/DeepSeek/Claude) as a quality check to strengthen QA documentation.”

“Built a Smart Resume Screening tool with a React frontend and a Python backend, owning most backend architecture and delivery. Implemented FastAPI endpoints for file upload and NLP/ML inference, created the end-to-end resume classification pipeline, logged predictions to a database for accuracy tracking, and deployed a Dockerized service optimized for low-latency, concurrent processing.”