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Silke Weißbach

Silke Weißbach

AI Annotator (Freelance, Remote, United Kingdom)

United Kingdom flagLondon, United Kingdom
$20.00/hrExpertAppenOther

Key Skills

Software

AppenAppen
Other

Top Subject Matter

Generative AI and machine learning model training
Legal Services & Contract Review
Regulatory Compliance & Risk Analysis

Top Data Types

VideoVideo
ImageImage
TextText
DocumentDocument

Top Task Types

Geocoding
Function Calling
Prompt Response Writing SFT
Audio Recording
Transcription
Bounding Box
Segmentation
Entity Ner Classification
RLHF

Freelancer Overview

AI Annotator (Freelance, Remote, United Kingdom). Brings 17+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Other. AI-training focus includes data types such as Image, Video, and Text and labeling workflows including Bounding Box, Segmentation, and Entity (NER) Classification.

ExpertEnglish

Labeling Experience

Appen

ANNOTATOR

AppenVideoGeocodingFunction Calling
I have contributed to ongoing MultiMango Diamond workstreams within TrainAI / RWS, focused on multimodal data evaluation across image, video, and text datasets. The scope includes large-scale comparative annotation and rubric-based ranking of AI-generated outputs. Tasks involve detailed assessment of colour fidelity, contrast accuracy, shadow density, spatial registration, framing consistency, artefact and residual detection, motion stability (video), and fine-detail resolution. I perform structured qualitative evaluations aligned with evolving project guidelines and technical scoring frameworks. The project volume includes continuous production across multiple Purchase Orders, with sustained high-accuracy delivery under deadline-driven conditions. Outputs are submitted within structured BPP systems and tracked through formal invoicing cycles. Quality measures adhered to include strict rubric compliance, internal consistency checks, edge-case flagging, guideline version tracking, an

I have contributed to ongoing MultiMango Diamond workstreams within TrainAI / RWS, focused on multimodal data evaluation across image, video, and text datasets. The scope includes large-scale comparative annotation and rubric-based ranking of AI-generated outputs. Tasks involve detailed assessment of colour fidelity, contrast accuracy, shadow density, spatial registration, framing consistency, artefact and residual detection, motion stability (video), and fine-detail resolution. I perform structured qualitative evaluations aligned with evolving project guidelines and technical scoring frameworks. The project volume includes continuous production across multiple Purchase Orders, with sustained high-accuracy delivery under deadline-driven conditions. Outputs are submitted within structured BPP systems and tracked through formal invoicing cycles. Quality measures adhered to include strict rubric compliance, internal consistency checks, edge-case flagging, guideline version tracking, an

2025 - 2025

AI Annotator (Freelance, Remote, United Kingdom)

OtherImageBounding BoxSegmentation
In this role, I annotated, evaluated, and curated diverse data types including text, images, video, and geographic information for generative AI and machine learning model training. I applied various labeling techniques such as bounding boxes, segmentation, and entity tagging, following detailed project guidelines and quality assurance processes. I also reviewed and scored AI-generated responses, performed QA checks, and delivered structured feedback to optimize workflows. • Consistently maintained high accuracy and productivity while adhering to project targets • Conducted research to support annotation accuracy and standardization across batches • Played a key role in inter-rater reliability assessment and ground truth dataset development • Provided valuable feedback to improve annotation processes and project documentation

In this role, I annotated, evaluated, and curated diverse data types including text, images, video, and geographic information for generative AI and machine learning model training. I applied various labeling techniques such as bounding boxes, segmentation, and entity tagging, following detailed project guidelines and quality assurance processes. I also reviewed and scored AI-generated responses, performed QA checks, and delivered structured feedback to optimize workflows. • Consistently maintained high accuracy and productivity while adhering to project targets • Conducted research to support annotation accuracy and standardization across batches • Played a key role in inter-rater reliability assessment and ground truth dataset development • Provided valuable feedback to improve annotation processes and project documentation

2025 - Present

Education

R

Royal College of Art

Master of Fine Arts, Painting

Master of Fine Arts
2018 - 2020
U

University of Fine Arts Hamburg

Bachelor of Arts, Sculpture

Bachelor of Arts
2016 - 2018

Work History

T

Timur Si-Qin

Studio Manager

London
2022 - Present
S

Stuart Haygarth

Studio Assistant

London
2020 - 2025