Data Annotation Lead

We need to output HTML fragment with sections: About the role? Actually the posting includes "About Mecka AI", "About Mecka", "Our Mission", "The role", "What You'll Do", "What You'll Bring", "Nice to have", "Inclusive Hiring at Mecka", "Use of Artificial Intelligence in Recruitment", "Compensation Range". We need to use headings for sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. However we must only include sections when posting has real specific content. We need to map content to these headings. We have: "About Mecka AI" and "About Mecka" (duplicate). Could be "About the role"? Actually "About Mecka AI" is about company, not role. The instruction: use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we should use those exact headings if we have content. We need to decide which sections we have content for. We have content about role: "The role", "What You'll Do", "What You'll Bring", "Nice to have". Could map to About the role (summary), Responsibilities (What You'll Do), Requirements (What You'll Bring + Nice to have?), Qualifications maybe overlapping, Skills maybe. Benefits: none given. Pay: we have Compensation Range: CA$100K - CA$135K. Schedule: not given (full-time on-site). Could infer schedule? The posting says "Full-time Location: NYC / Toronto — on-site". That implies schedule: full-time, on-site. Should we include Schedule section? It says only include if posting actually states them. It does state full-time and on-site, which is schedule info. So we can include Schedule with that info. Benefits: none stated, so omit. Pay: we have compensation range, include Pay. Qualifications: Could combine What You'll Bring (required) and Nice to have. But we need to avoid filler. We'll create Qualifications section with required and nice-to-have bullet lists. Skills: maybe not needed if we already have Qualifications. But we could include Skills if we have specific skill statements. The posting includes "Direct experience in data annotation / labeling (required)", "Ideal background in data collection, physical AI / robotics, or text annotation", "Proven people and operations leadership", "PM instincts", "Clear written and verbal communication", "Comfort with annotation tooling and the ability to leverage AI coding tools", "Intermediate understanding of ML", "A level of hardcore-ness while still treating people like people". Those are skills/qualifications. Could put them under Qualifications. We need to avoid duplicate content. We'll produce sections: About the role (summary from "The role" paragraph), Responsibilities (What You'll Do), Qualifications (What You'll Bring + Nice to have), Pay (Compensation Range), Schedule (Full-time, on-site). Also maybe include About the company? Not required headings; we could omit as not in list. The instruction says use those headings for sections; we can also include other headings? It says use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It implies we should use those headings; we could also use other headings if needed but better to stick to those. So we will not include "About Mecka AI" etc as separate headings; we can incorporate that info into About the role? But About the role should be about the role, not company. However we could include a brief About the role paragraph that includes company context? Might be okay. We must preserve ALL substantive information; do not invent or summarize away detail. So we need to keep all details from the posting. If we omit sections like About Mecka AI, we would lose that info. But we could embed that info within About the role section? The instruction says do NOT repeat the job title as a heading (the page already shows it) and do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

or drop it. It doesn't forbid other headings besides the listed ones, but says use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It suggests those are the expected headings; we could still use other headings if needed, but better to follow the pattern. We need to preserve all substantive information: company description, mission, etc. Where to put? Could be part of About the role? But that would mix company info with role. Might be acceptable as it's still substantive. However the instruction says "About the role" heading example; maybe they expect a short paragraph about the role. But we can still include company info under that heading; it's still about the role within the company. Alternatively we could add an additional heading like "About Mecka AI" but that's not in the list; risk of being considered not following instruction. Safer to embed within About the role. We must not create sections with filler like "commensurate with experience". We have real content for Pay and Schedule. Let's extract details: Company description: "Mecka AI is building the data infrastructure layer for robotics and embodied AI. We design and operate global systems for data capture, data labeling, and hardware-enabled workflows used by leading AI labs and robotics companies to train and validate humanoid and embodied AI systems. We work closely with frontier robotics teams to bridge real-world data, simulation, learning-based systems, and deployed hardware." Second paragraph about Mecka (duplicate): "Mecka AI is building the data infrastructure layer for robotics and embodied AI. We design and operate global systems for data capture, data labeling, and hardware-enabled workflows used by leading AI and robotics teams. Our operations span multiple countries, with contributors, partners, and customers across North America and Asia." Mission: "Robotics will become the largest industry in human history — larger than anything that has come before it. As intelligent machines move into the physical world, they will dramatically expand global GDP, raise the material standard of living for everyone, and ultimately help make humanity a multiplanetary civilization. None of that happens without one thing: enormous amounts of high-quality, real-world data. Mecka AI builds that foundation. We are the data infrastructure layer for robotics and embodied AI — the substrate that teaches machines to perceive, reason, and act in reality. Get this right, and we accelerate the most important technological transition of our time." The role paragraph: "We're looking for a Data Annotation Lead to own our annotation operation end-to-end and build the team behind it. This is a lead / player-coach role with a heavy PM lean: you'll set the framework, quality bar, and tooling for annotation, turn ambiguous research requests into crisp guidelines, and scale a workforce that can pivot fast without dropping quality. You'll sit at the seam of ML/CV, product, and operations." What You'll Do bullet list (actually sentences): - Own annotation operations end-to-end — quality, throughput, and cost per delivered hour - Build and lead the in-house annotation team; own the in-house vs. partner/BPO mix and manage external vendors where used - Translate research and client requirements into clear annotation guidelines, taxonomies, and QA rubrics - Stand up the quality system: audits, inter-annotator agreement, golden sets, reviewer scorecards, escalation paths - Partner with ML/CV and product to spec and pilot new annotation task types for fast-moving experiments - Drive AI-assisted labeling (model pre-labels → human correction) to raise throughput and cut cost - Own the metrics — dashboards on quality and volume — and report the state of annotation to leadership - Stay in the weeds: annotate yourself whenever a new task type is being designed What You'll Bring (required): - Direct experience in data annotation / labeling (required — the thing we care most about) - Ideal background in data collection, physical AI / robotics, or text annotation - Proven people and operations leadership — you've built or scaled a team or function - PM instincts: ruthless prioritization of competing requests, organized execution under ambiguity, strong stakeholder management across annotators, engineering, and clients - Clear written and verbal communication — your guidelines are the source of truth for the team - Comfort with annotation tooling and the ability to leverage AI coding tools to build internal trackers/dashboards (no formal CS background required) - Intermediate understanding of ML and how annotation quality drives model performance - A level of hardcore-ness while still treating people like people Nice to have: - Previously led a data annotation team, or were a top-tier annotator yourself - Vendor / BPO management experience, ideally where quality was the primary lever - Familiarity with text annotation styles and video concepts (frame rate, keypoints, bounding boxes, temporal segments) - Experience managing distributed or offshore teams Inclusive Hiring at Mecka: paragraph about accommodation, equal opportunity. Use of Artificial Intelligence in Recruitment: paragraph about AI use. Compensation Range: CA$100K - CA$135K Also location: NYC / Toronto — on-site. Type: Full-time. We need to include Schedule: Full-time, on-site. Pay: compensation range. We need to avoid boilerplate: Inclusive Hiring and AI in Recruitment are boilerplate? They are about hiring process; could be considered boilerplate but they are substantive? The instruction says remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. Inclusive Hiring and AI in Recruitment are EEO/equal-opportunity and AI usage statements; likely considered boilerplate to remove. So we should omit those sections. Also we should remove duplicated lines: The "About Mecka AI" and "About Mecka" are similar; we can combine. We must preserve all substantive information: company description, mission, role description, responsibilities, qualifications, nice-to-have, compensation, location, schedule. Thus final HTML:

About the role

Mecka AI is building the data infrastructure layer for robotics and embodied AI. We design and operate global systems for data capture, data labeling, and hardware-enabled workflows used by leading AI labs and robotics companies to train and validate humanoid and embodied AI systems. We work closely with frontier robotics teams to bridge real-world data, simulation, learning-based systems, and deployed hardware. Robotics will become the largest industry in human history — larger than anything that has come before it. As intelligent machines move into the physical world, they will dramatically expand global GDP, raise the material standard of living for everyone, and ultimately help make humanity a multiplanetary civilization. None of that happens without one thing: enormous amounts of high-quality, real-world data. Mecka AI builds that foundation. We are the data infrastructure layer for robotics and embodied AI — the substrate that teaches machines to perceive, reason, and act in reality. Get this right, and we accelerate the most important technological transition of our time.

We're looking for a Data Annotation Lead to own our annotation operation end-to-end and build the team behind it. This is a lead / player-coach role with a heavy PM lean: you'll set the framework, quality bar, and tooling for annotation, turn ambiguous research requests into crisp guidelines, and scale a workforce that can pivot fast without dropping quality. You'll sit at the seam of ML/CV, product, and operations.

Responsibilities

• Own annotation operations end-to-end — quality, throughput, and cost per delivered hour
• Build and lead the in-house annotation team; own the in-house vs. partner/BPO mix and manage external vendors where used
• Translate research and client requirements into clear annotation guidelines, taxonomies, and QA rubrics
• Stand up the quality system: audits, inter-annotator agreement, golden sets, reviewer scorecards, escalation paths