Abdul Rehman A.Private profile: Upwork shows its earnings only to signed-in members, so we check it every few weeks, not daily. MRR here is a rough estimate (Upwork's six-month earnings ÷ months active). Last read Sep 25, 2026.

I help AI product teams ship reliable, safe, and enterprise-ready ML/LLM systems by building rigorous evaluation and testing from data to deployment. Most AI failures aren’t “model problems”—they’re silent data issues, brittle pipelines, and missing production-focused tests. I design evaluation frameworks that surface real-world risks (hallucinations, retrieval gaps, bias, regressions, tool/agent failure modes) and translate findings into fast, actionable fixes. 𝗖𝗼𝗿𝗲 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀 • 𝗗𝗮𝘁𝗮-𝗖𝗲𝗻𝘁𝗿𝗶𝗰 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 (𝗧𝗿𝘂𝘀𝘁 𝘁𝗵𝗲 𝗱𝗮𝘁𝗮 𝗯𝗲𝗵𝗶𝗻𝗱 𝘆𝗼𝘂𝗿 𝗺𝗼𝗱𝗲𝗹𝘀)   1. Dataset validation & quality checks   2. Drift detection (data + feature drift)   3. Leakage, labeling consistency, schema/constraint validation   4. Detect issues before training, not after deployment • 𝗠𝗼𝗱𝗲𝗹-𝗖𝗲𝗻𝘁𝗿𝗶𝗰 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 (𝗠𝗲𝗮𝘀𝘂𝗿𝗲 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝗯𝗲𝗵𝗮𝘃𝗶𝗼𝗿)   1. Performance evaluation aligned to production risks   2. Fairness & bias audits   3. Robustness testing (edge cases, stress tests, distribution shifts) • 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗘𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻 (𝗔𝗱𝘃𝗲𝗿𝘀𝗮𝗿𝗶𝗮𝗹 & 𝗥𝗲𝗱-𝗧𝗲𝗮𝗺 𝗧𝗲𝘀𝘁𝗶𝗻𝗴)   1. Adversarial scenario design to expose high-impact failure modes   2. Red teaming for safety, policy, and misuse risks   3. Testing multi-step agentic workflows and tool-use behaviors • 𝗥𝗔𝗚 & 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀 (𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 + 𝗴𝗿𝗼𝘂𝗻𝗱𝗶𝗻𝗴 + 𝗵𝗮𝗹𝗹𝘂𝗰𝗶𝗻𝗮𝘁𝗶𝗼𝗻 𝗿𝗶𝘀𝗸)   1. Retrieval evaluation: relevance/recall, latency, index quality   2. Generation evaluation: grounding & citation checks, hallucination testing   3. Coverage testing across query types, workloads, and failure conditions   4. Full pipeline assurance: retrieval → rerank → context → generation → post-processing 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝗮𝗯𝗹𝗲𝘀   • Evaluation Reports: concise, prioritized findings across data, models & pipelines   • Targeted Weakness Detection: what breaks, why, and how to reproduce   • Fix Plans / Roadmaps: remediation steps your team can implement quickly   • CI/CD Test Suites: automated eval gates integrated into your pipelines   • Governance & Guardrails: safety monitoring, oversight, and responsible AI controls LLM evaluation, RAG evaluation, AI testing, ML testing, prompt evaluation, hallucination testing, grounding, citation checking, retrieval evaluation, red teaming, adversarial testing, agent testing, reliability engineering, model monitoring, data drift, dataset validation, fairness, bias audit, robustness, CI/CD, MLOps, eval harness, test automation