Syed Fakhr E Ali

If your AI model isn’t performing well, bad training data might be the reason. That’s where I come in.

I work with AI startups and ML teams to deliver clean, high-quality annotations — fast and hassle-free.

Whether you're building a self-driving car, a content filter, a fashion or sports recommender — I’ve got your data covered.

With 4+ years of experience, I focus on:

→ Object detection, image segmentation & labeling + text annotation.

→ Audio labeling and Audio speaker diarization labeling

→ Categorization, fact-checking and transcription

→ Tools like Labelbox, CVAT, and MTurk

→ Standards like YOLO and PASCAL VOC

I've supported teams across industries like automotive, fashion, sports and social media AI, helping them scale with confidence.

If you're tired of messy datasets and fixing errors, let’s team up.

You bring the models — I’ll bring the clean data.

AAI (Audi's Project) Mar 2021 - Present

Data Labeling Technician & Quality Analyst

Oversaw data labeling operations for Audi's Project at AAI, ensuring precision and accuracy in data annotation. Implemented quality control measures to maintain high standards in data labeling and analysis, contributing to the project's success. Utilized advanced analytical tools and techniques to identify and rectify discrepancies in labeled data, enhancing data quality and reliability.

 Collaborated closely with cross-functional teams to optimize data labeling processes and improve efficiency.

 Conducted data audits and assessments to evaluate labeling procedures and identify areas for improvement.

 Provided feedback to stakeholders based on data analysis quality assessment and improvement initiatives.

 Demonstrated problem-solving skills in resolving complex data labeling challenges and ensuring data accuracy.

 Participated in team meetings and training sessions to foster collaboration in data labeling and quality assurance.

Video Data Annotation - Describe a movie scene in detail Feb - Feb 2024

Engaged in annotation of movie scenes, meticulously describing intricate details and nuances. Employed keen observational skills to capture the essence of each scene, including character actions, emotions, and settings. Utilized industry-standard annotation tools to provide accurate and detailed descriptions of visual elements.

 Ensured consistency and clarity in scene descriptions, adhering to project guidelines and standards.

 Collaborated with team of annotators to enhance the accuracy and comprehensiveness of scene annotations.

 Demonstrated proficiency in cinematic techniques and storytelling devices to convey scene dynamics.

 Maintained a high level of attention to detail to capture subtle nuances and subtext within movie scenes.

Syed Fakhr E A. Page 2

 Contributed to the development of datasets used for training machine learning models in scene understanding and video analysis applications.

Sport Video Labeling | Rugby Analysis 2024

Analyzed rugby video footage with precision to identify key player movements and strategic plays. Utilized advanced video labeling techniques to categorize various aspects of rugby matches, including tackles, passes, and scrums. Employed cutting-edge technology to enhance the accuracy and efficiency of rugby analysis.

 Collaborated with a team of experts to ensure comprehensive and insightful labeling of sports videos.

 Demonstrated proficiency in sports terminology and understanding of rugby gameplay dynamics.

 Generated detailed reports summarizing key findings and insights from the video labeling process.

 Implemented rigorous quality control measures to maintain the integrity and reliability of labeled data.

 Contributed to the improvement of rugby analysis algorithms by providing valuable labeled data inputs.

Image Annotation of Arial Images 2023

Utilized advanced labeling techniques to mark specific objects and areas within the images, ensuring accuracy and consistency.

Demonstrated proficiency in image interpretation and understanding of geographical contexts to provide relevant annotations. Collaborated with the team to meet project deadlines and deliver high-quality labeled datasets for model training.

 Leveraged expertise in geospatial analysis to ensure the suitability of annotated data for model training purposes.

 Applied advanced image processing techniques to optimize the clarity and utility of labeled images.

 Received a stellar rating of 5 out of 5 for consistently delivering exceptional results.

 Maintained confidentiality and security of labeled data throughout the annotation process.

 Displayed adaptability and a commitment to continuous improvement by staying updated on emerging labeling methodologies and technologies.

Maanz AI SMC Private Limited Mar 2021 - Nov 2023

Data Annotator & Quality Assurance Specialist

Spearheaded data annotation and quality assurance initiatives for prestigious clients Audi and Lamborghini to Object Detection (OD),

Scene Recognition (MSR), and Lane Detection (LDA) projects. Annotated and ensured high-quality labeling of data for Audi's OD, MSR,

and LDA projects, and Lamborghini's OD, fostering accurate computer vision algorithms.

 Managed large datasets daily, overseeing quality assurance of thousands of images with precision and efficiency.

 Conducted training sessions for multiple batches, totaling 10-15 employees each on projects such as MOD LDA in knowledge transfer and team development.

 Exhibited leadership prowess by training 50-plus employees for the MSR project and overseeing 90-plus employees for MOD project.

 Oversaw annotation process for complex data sets, ensuring precision and accuracy in labeling for various AI projects.

 Implemented quality assurance protocols to maintain the highest standards of data integrity and reliability.

 Collaborated with project managers and developers to understand annotation requirements for process improvement.

 Identified and resolved discrepancies in labeled data, employing meticulous attention to detail and problem-solving skills.

 Contributed to team meetings and brainstorming sessions to enhance annotation strategies and workflows.

 Demonstrated adaptability and flexibility in managing shifting project priorities and tight deadlines, consistently delivering high quality annotated data on time.

B.com, NTI, Discontinued

Superior College,2018

Associate's degree, Business/Commerce, General

Executive Guide to Human-in-the-Loop Machine Learning and Data Annotation, 2024