Open to AI training, evaluation & applied AI roles

AI TRAINING · MODEL EVALUATION · APPLIED AI · DATA ANALYTICS

I turn complex AI systems into reliable, useful experiences.

Artificial Intelligence graduate with 3+ years of remote experience training and evaluating generative AI in Arabic and English, plus hands-on work in multi-agent LLM systems, real-time computer vision, analytics, and technical project delivery.

3+years AI training & evaluation
9specialized LLM agents in flagship project
AR / ENmultilingual evaluation workflows

ahmed.ai / focus

CURRENT PROFILE

Human judgment for AI.
Engineering for impact.

Model Evaluation96%
Arabic Localization94%
Applied AI Systems91%
Evaluation8D / 10D
FocusQuality
BasedEgypt
StatusAvailable
RLHFModel EvaluationArabic LocalizationAI SafetyComputer VisionMulti-Agent LLMsPower BIData Quality RLHFModel EvaluationArabic LocalizationAI SafetyComputer VisionMulti-Agent LLMsPower BIData Quality
01

ABOUT

Technical depth.
Clear communication.

I’m an Artificial Intelligence graduate from the Faculty of Computers and Artificial Intelligence, Benha University. My work combines AI engineering, human-data quality, language judgment, analytics, and practical problem solving.

I’m comfortable moving between technical and non-technical contexts — from evaluating model reasoning and coding outputs to presenting complex AI concepts clearly to audiences without a technical background.

I also bring around four years of hands-on project-management experience through university and online projects, coordinating deliverables, dividing work, presenting outcomes, and keeping teams aligned around deadlines.

Download full résumé
02

AI TRAINING & EVALUATION

Professional work where quality is the product.

Remote, rubric-driven AI workflows spanning model behavior, multilingual quality, safety, data annotation, coding, voice, and localization.

S

2023 — PRESENT

AI Trainer & Data Quality Specialist

Scale AI / Outlier

Training and evaluating generative AI through structured feedback, rubric-based scoring, multilingual review, and human-in-the-loop quality processes.

  • Evaluate model outputs across multidimensional 8D / 10D frameworks covering correctness, relevance, clarity, completeness, safety, fluency, cultural context, and instruction-following.
  • Review reasoning, coding solutions, data-science outputs, prompts, and annotations for logical, factual, technical, and guideline-compliance issues.
  • Create and refine rubrics, identify edge cases and inconsistent labels, and document precise corrections that improve reviewer alignment and training-data quality.
  • Contribute across text, image, audio, voice, translation, transcription, classification, localization, and model-output evaluation tasks.
RLHFRubricsQAReasoningCodingVoice
H

2026 — PRESENT

AI Trainer — Arabic Localization & Safety

Handshake

Adapting AI training content into natural Arabic while protecting intent, policy constraints, cultural relevance, and evaluation consistency.

  • Translate and localize English AI-training material into natural, country-appropriate Arabic while preserving meaning, formatting, safety constraints, and task intent.
  • Evaluate model responses for policy compliance, linguistic accuracy, relevance, safety, and instruction-following across multilingual workflows.
  • Flag ambiguous guidelines, inconsistent labels, and quality defects, then provide structured corrections that support reliable reviewer decisions.
  • Apply strong Arabic language judgment across Modern Standard Arabic and regional dialect contexts.
ArabicLocalizationSafetyPolicyLinguistic QA
03

FEATURED PROJECTS

Applied AI built around real users.

Selected work across intelligent coaching systems and business analytics, with the focus on system design, decision-making, and practical outcomes.

FLAGSHIP · GRADUATION PROJECT

AI Fitness Coach

Multi-Agent LLMComputer VisionAdaptive PlanningReal-Time Feedback

An intelligent fitness-coaching platform designed as more than a pose tracker. The system combines a multi-agent LLM architecture with real-time computer vision to build personalized plans, monitor execution, evaluate progress, and continuously adapt recommendations as the user changes.

SYSTEM ARCHITECTURE9 specialized AI agents + vision feedback loop
INPUTUser profile & progressGoals · body changes · history · performance
ORCHESTRATION9-Agent LLM SystemSpecialists coordinate around the user
OUTPUTAdaptive Coaching PlanContinuously revised recommendations

01 · MULTI-AGENT INTELLIGENCE

Specialized agents, one coordinated plan.

The LLM layer is structured around nine specialized agents rather than a single generic assistant. Individual agents own focused coaching responsibilities — including areas such as nutrition and workout planning — while the wider system combines their outputs into a coherent user plan.

The plan is not static: recommendations can be revised as the user progresses, performance changes, or new body measurements and conditions are introduced.

02 · REAL-TIME COMPUTER VISION

Form evaluation while the exercise is happening.

The vision component tracks body pose during exercise, evaluates movement and joint alignment, and identifies form issues in real time. Instead of only counting repetitions, the system is designed to produce specific corrective feedback when posture deviates from the expected movement.

That means feedback can respond to details such as an elbow drifting inward or outward, helping the user correct technique during the set rather than after it.

03 · CLOSED FEEDBACK LOOP

Observe → evaluate → adapt.

Training behavior and user progress feed back into the coaching layer. The concept links what the user is prescribed with what the user actually performs, allowing the system to support a more adaptive coaching experience over time.

The project required integrating AI model behavior, computer-vision logic, user-facing feedback, and team-level project execution into one end-to-end product concept.

BUSINESS INTELLIGENCE · MICROSOFT SAMPLE DATA

AdventureWorks Analytics Dashboards

Interactive Power BI dashboards built using Microsoft’s AdventureWorks sample data to turn relational business data into decision-ready reporting. The work covered data preparation, modeling, calculated measures, KPI design, drill-through interactions, tooltips, and visual storytelling.

Power QueryData cleaning & transformation
Data ModelRelationships & analytical structure
DAXMeasures, KPIs & business logic
Power BIInteractive dashboards & reporting

AdventureWorks / Executive View

•••
Revenue↑ KPI
OrdersTrend
MarginMix
Sales performanceProduct mixRegional KPIs
04

CAPABILITIES

A hybrid AI + data + communication toolkit.

Technical execution backed by analytical thinking, structured problem solving, communication, and project ownership.

01

AI Training & Evaluation

RLHF · Model Output Evaluation · Data Annotation · 8D/10D Scoring · Rubric Development · QA · Error Analysis · Guideline Review · Human-in-the-Loop AI

02

Applied AI & Engineering

Python · Machine Learning · Deep Learning · Computer Vision · NLP · LLM Workflows · Data Preprocessing · Model Evaluation · C++ · Java

03

Analytics & BI

Power BI · Power Query · DAX · Excel · SQL · Pandas · NumPy · Data Cleaning · Data Modeling · KPI Reporting · Dashboards · Visualization

04

Language & Quality

Arabic Localization · MSA & Regional Dialects · Translation · Linguistic QA · Voice Recording · Transcription · Safety Evaluation · Prompt Review

05

Problem Solving

Analytical thinking · Error detection · Edge-case analysis · Structured reasoning · Root-cause thinking · Technical review · Detail orientation

06

Leadership & Communication

Project management · Team coordination · Presentations · Public speaking · Technical-to-non-technical explanation · Distributed teamwork · Deadline ownership

05

EDUCATION

BENHA UNIVERSITY · JUNE 2026

Bachelor of Artificial Intelligence

Faculty of Computers and Artificial Intelligence

Overall GradeVery Good

LET’S BUILD SOMETHING USEFUL

Need someone who can understand the model, the data, and the user?

I’m open to remote opportunities in AI training, model evaluation, data quality, Arabic localization, analytics, and applied AI.