Vetted Data Validation Professionals

“QA Engineer focused on web and mobile applications (not game industry) who partners closely with developers and product managers from early SDLC through release. Notably caught a critical e-commerce/payment defect where orders appeared successful in the frontend but were missing in the backend, validating via SQL queries and providing evidence-rich Jira reports.”

Nicholas Farrel

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Mid-level QA Tester and Game Designer specializing in game QA and 3D character animation

Tangerang Selatan, Indonesia9y exp

“Console game QA tester with experience primarily on Xbox, focused on manual testing of twin-stick and arcade-style games (input breaking, stage clearing) and executing checklist-driven test passes tracked in spreadsheets. Familiar with major platform certification checklist names (TRC/XR/LOT) and prioritizes issues based on impact to players and the development team.”

Diego Hernandez

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Entry-level Mechatronics Engineer specializing in robotics, automation, and ROS 2

Cali, Colombia

“Robotics software/embedded engineer who helped build an end-to-end perception sensor platform in a two-person team, owning PCB design, ROS architecture (sensor/processing/diagnostic nodes), and documentation. Experienced integrating heterogeneous sensors over CAN with Arduino and optimizing real-time performance bottlenecks (camera and high-frequency streams) using compression, grayscale pipelines, and reduced inference frequency; also containerized the system with Docker.”

“Entry-level analytics candidate with hands-on experience in education data, combining SQL, Python, and Tableau to build reporting tables, reproducible workflows, and dashboards for student engagement and performance. Stands out for translating messy multi-source data into practical tools that helped academic teams identify at-risk students earlier and target support more effectively.”

“Backend-focused developer who built LinguaTile (language learning app) on a FastAPI + MongoDB monolith deployed to Google Cloud Run, emphasizing async performance and security (RBAC/JWT, rate limiting, request tracing). Also created Mark-RS, a static HTML generator with a 100% CommonMark-compliant Markdown parser, demonstrating strong edge-case rigor and systems robustness.”

Kumar Manik

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

0y exp

“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.”

“Candidate stands out for treating AI as a structured productivity and coordination layer rather than just a coding assistant. They describe using role-based multi-agent workflows across research, planning, technical execution, QA, security, and documentation, with a strong emphasis on human review and production validation.”

“Salesforce-focused candidate with hands-on experience improving opportunity pipeline governance, reporting accuracy, and sales workflow usability in Sales Cloud. They demonstrate practical platform depth across validation rules, flows, LWC, Aura, Apex, and Salesforce security, with a clear modernization mindset toward scalable and maintainable solutions.”