Peter M.

Key Skills

Software

No software listed

Top Subject Matter

Digital imaging

Retouching Domain Expertise

color grading

Top Data Types

Image

Text

Top Task Types

Prompt + Response Writing (SFT)

Freelancer Overview

Digital Retoucher & Post-Production Specialist (AI-relevant visual evaluation/edge-case detection). Brings 6+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Adobe Photoshop, Lightroom Classic, and Capture One. Education includes Bachelor of Arts, Obafemi Awolowo University (2020). AI-training focus includes data types such as Image and Text and labeling workflows including Evaluation, Rating, and Prompt + Response Writing (SFT).

Labeling Experience

Lead Photographer & Creative Strategist (prompt optimization and QA for multimodal AI training)

OtherTextPrompt + Response Writing (SFT)

Translated complex visual themes into descriptive, parameter-driven prompt content that mirrors text-to-image prompt architecture. Reverse engineered high-end visual aesthetics (e.g., cinematic storytelling, golden hour, high-contrast editorial) into actionable textual breakdowns for training and evaluation use cases. Enforced strict consistency between creative direction and the technical parameters implied by the descriptions.•Prompt optimization via aesthetic-to-parameter breakdowns•Nuanced textual articulation of lighting, composition, and style attributes•Quality-focused consistency checks on descriptive prompt outputs•Support for RLHF-style improvement by identifying likely image generation failure points

2021 - Present

Digital Retoucher & Post-Production Specialist (AI-relevant visual evaluation/edge-case detection)

Image

Provided expert visual QA by critiquing, evaluating, and correcting optical anomalies such as color casts, exposure errors, and anatomical distortions in large image batches. Assessed image quality at a pixel level to ensure premium branding consistency and realistic reconstruction of shadows, highlights, and micro-textures. Applied disciplined standards to detect edge-case defects in complex textures, backgrounds, and lighting compositions.•Critique and correction of high-volume image batches for quality issues•Frequency separation, color grading, and non-destructive pixel-level manipulation to meet standards•Reconstruction of realistic lighting geometry (strobes, ambient modifiers)•Detection of micro-defects relevant to AI image quality assessment

2021 - Present

Education

Work History