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REQUIREMENT_ID_168 • 3-DAY_ACTIVE_POLICY

AI Facial Data Collection Associate

Company
Company jobs.micro1.ai
Type
Opportunity Type Full-Time Job
Salary
Stipend / Salary $139 - $140/hr
Location
Location Remote
Posted Date
Posted Date Yesterday
Selfies Video recordings Attention to detail Follow instructions
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Aptitude Practice Questions Open Resource ↗
Helps you sharpen quantitative and logical reasoning skills useful for any screening test.
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Company Interview Preparation Guide Open Resource ↗
Provides insights into common interview formats and questions asked by tech‑data firms.
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Interview Preparation Resources Open Resource ↗
Offers curated notes, mock interview tips, and resume building advice for remote contract roles.
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Algorithm Problem Set Open Resource ↗
Contains coding challenges to keep problem‑solving skills sharp, beneficial for technical assessments.

Applicants must be 50 years of age or older (no upper age limit). No specific degree or academic qualification is required, but candidates should possess a valid government‑issued ID for age verification. Must have a functional smartphone or digital camera capable of capturing high‑resolution images and videos. Must be able to provide clear, unedited selfies and video recordings from the past five years. No backlogs or disciplinary issues are applicable as this is a freelance contract role.

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Round 1: Application review and age verification
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Round 2: Sample media submission and quality check
3
Round 3: Final approval and payment processing
Micro1.ai is an emerging AI‑focused data platform that partners with global technology firms to build high‑quality training datasets for computer‑vision, speech, and natural‑language models. Founded by a team of data scientists and engineers, the company operates a fully remote workforce, leveraging talent from across India and beyond. Its mission is to democratise AI by ensuring that training data reflects the diversity of real‑world users, and it has quickly become a trusted vendor for several Fortune‑500 AI product teams. The culture at Micro1.ai is built around flexibility, inclusivity, and a strong emphasis on data integrity; employees enjoy a results‑only work environment, regular virtual knowledge‑sharing sessions, and clear pathways for skill development. The role of AI Facial Data Collection Associate (also referred to as AI Facial Data Collection Contributor) is a remote, contract‑based position designed specifically for contributors aged 50 years or older. As a contributor, you will help enrich the facial‑recognition training pipeline by providing authentic, unedited visual content captured over the past five years. This data will be used to improve the accuracy and fairness of AI models that power everything from security systems to mobile applications. The engagement is short‑term, with a one‑time payment upon successful submission of the required assets. Key Responsibilities: 1. Capture and submit 30 high‑resolution, unedited selfies taken within the last five years. 2. Capture and submit 10 short video clips (minimum 10 seconds each) taken within the last five years. 3. Ensure all media are free from filters, beautification apps, or any post‑processing edits. 4. Follow detailed submission guidelines provided by the project manager. 5. Verify that each file meets the required format, resolution, and naming conventions. 6. Report any technical issues or ambiguities promptly to the support team. 7. Incorporate feedback from the quality‑control team and resubmit any rejected assets. 8. Maintain confidentiality of the project and refrain from sharing any proprietary instructions. 9. Keep a log of submission timestamps for audit purposes. 10. Complete a brief post‑submission questionnaire about the experience. Tech Stack & Tools: The role does not require programming skills; contributors will use a smartphone or digital camera, a secure web portal for uploads, and basic file‑format conversion tools if needed. The platform employs end‑to‑end encryption to protect personal data. Growth Path: While this is a contract gig, high‑performing contributors may be invited to join longer‑term data‑annotation projects, mentor newer contributors, or transition into remote quality‑assurance roles within Micro1.ai. Why Join: This opportunity offers a generous hourly rate for a simple, home‑based task, flexible timing, and the chance to be part of a cutting‑edge AI initiative that values the perspectives of senior citizens. It also provides a safe, remote work environment with clear payment terms and no hidden fees.

jobs.micro1.ai — AI & Machine Learning Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC 📖
Aptitude Practice Questions & Online Mock Tests

Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.

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COMPANY GUIDE 🎯
jobs.micro1.ai Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for jobs.micro1.ai and off-campus tech roles.

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MOCK TESTS & PAPERS 📝
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

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CODING PRACTICE 💻
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

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Round 1: Online Assessment (OA)
Aptitude, Quantitative Logic & 2 Coding Problems
Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1
Core Tech Stack (Selfies, Video recordings, Attention to detail, Follow instructions) & Live Code Tracing
Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving
Database Schemas, APIs & Architecture Basics
Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion
jobs.micro1.ai Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
What is the bias-variance tradeoff and how do you prevent overfitting? Answer ▼
Model Answer: High bias leads to underfitting (oversimplified model), high variance leads to overfitting (captures noise). Mitigate using L1/L2 Regularization, Dropout, Cross-Validation, and data augmentation.
Explain the difference between Precision, Recall, and F1-Score. Answer ▼
Model Answer: Precision = TP / (TP + FP) (correctness of positive predictions). Recall = TP / (TP + FN) (coverage of actual positives). F1-Score is the harmonic mean of Precision and Recall.
How does Gradient Descent work and what is the role of Learning Rate? Answer ▼
Model Answer: It optimizes loss functions by iteratively moving weights in the direction of negative gradient. A large learning rate may overshoot the minimum; a small rate causes slow convergence.
What is the difference between Supervised, Unsupervised, and Self-Supervised learning? Answer ▼
Model Answer: Supervised uses labeled data (X -> y). Unsupervised finds hidden patterns in unlabeled data (clustering/PCA). Self-supervised generates labels from input data (e.g. masked language modeling in BERT/Transformers).
Why do you want to join jobs.micro1.ai as a AI Facial Data Collection Associate?
Preparation Tip: Highlight jobs.micro1.ai's market reputation, recent tech innovations, and how your skills in Selfies directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Preparation Tip: Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.

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