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Faisal Javed
Senior AI/ML Engineer specializing in LLMs, MLOps, and AWS
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About
Built a production ad-spend optimization system that combined deterministic audit logic with LLM-generated explanations, surfacing severe inefficiencies including 70-90% wasted spend in some Google Ads accounts. Stands out for pairing measurable business impact with pragmatic AI safety and usability decisions, including approval-gated execution and structured, human-readable recommendations.
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Key Strengths
- Built end-to-end production ML/AI optimization system for Google Ads scheduling
- Strong business-impact orientation with pre/post measurement
- Identified 70-90% wasted ad spend in some accounts
- Detected approximately $3,300 waste out of $3,700 in one account
- Pragmatic hybrid architecture combining deterministic logic with LLM explanations
- Careful AI safety design with approval-gated actions and no autonomous model control
- Improved usability by converting raw datasets into structured flagged results and recommendations
- Built reusable Python CLI toolkit used by multiple engineers
- Emphasis on deterministic, testable systems with strict input/output validation
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