Data Collection Lead, AI/ML Data Programs

Job not on LinkedIn

🔥 3 minutes ago

🌐 Brazil, India, +2 more countries – Remote

🇧🇷 Brazil – Remote 🇮🇳 India – Remote 🇧🇩 Bangladesh – Remote 🇿🇦 South Africa – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

👻 Ghost score 22%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Whitecollars

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2018

🎯 Recruiter

👥 HR Tech

🤝 B2B

Recruitment • HR Tech • B2B

Whitecollars is a UK-headquartered recruitment consultancy that helps companies hire global, vetted talent on a flat-fee, no-commission model. They source candidates across 35+ countries, use a structured three-layer vetting process, and deliver vetted shortlists with interview insights and video recordings—typically within 7–10 days. Whitecollars offers replacement guarantees of up to 12 months, pay-only-if-you-hire pricing, and services for both employers (flat-fee recruitment for permanent and contract roles) and jobseekers (end-to-end job search support). They operate from London with a MENA branch in Cairo and position themselves as a cost-predictable, faster alternative to traditional recruitment agencies.

📋 Description

• Manage assigned data collection projects from initiation through final delivery • Translate client requirements into structured plans, timelines, milestones, and execution workflows • Design collection strategies defining participant profiles, geographic coverage, devices, environments, metadata requirements, and quality criteria • Run pilot collections, assess results, identify operational gaps, and refine methodologies before production scaling • Identify, evaluate, and coordinate freelancers, field resources, communities, agencies, and external vendors • Plan resources and capacity, monitor performance, and adjust resource allocation • Establish quality-control workflows and validate collected data against client specifications • Identify recurring data issues and manage corrective actions, rejections, and recollection • Communicate with clients about requirements, progress, risks, feasibility, and operational challenges • Monitor commitments, dependencies, costs, and delivery risks; resolve bottlenecks and escalate concerns • Document methodologies and build reusable SOPs, templates, and checklists • Continuously improve collection workflows and strengthen AI data operations across domains, geographies, and data modalities

🎯 Requirements

• 3–5 years of experience in project management, data operations, or a related field • Direct exposure to egocentric AI data collection projects • Experience with image and video collection, speech and audio recording, multilingual datasets, computer vision, multimodal data, or LLM and generative AI projects • Experience with Human-in-the-Loop operations and AI/ML data requirements is a significant advantage • Experience coordinating distributed teams and external resources • Experience evaluating vendors and mobilizing resources quickly • Ability to balance quality, cost, timelines, and feasibility • Strong client communication and stakeholder management skills • Ability to clarify requirements, explain implications, and recommend workable alternatives • Root-cause analysis and process improvement skills • Resourcefulness, structured execution under pressure, and proactive risk management • Bachelor's degree in Business, Operations, Technology, Computer Science, or a related field

🏖️ Benefits

• End-to-end ownership of data collection projects • Exposure to diverse AI programs, data modalities, industries, geographies, and collection challenges • Direct impact on AI development through high-quality datasets • Opportunity to develop reusable methodologies and improve operational workflows • Cross-functional collaboration with clients, internal teams, freelancers, and external vendors • Professional growth in project leadership, distributed resource management, data quality, and AI/ML operations • Fully remote work flexibility • Collaboration with a globally distributed team