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- The image and video datasets that train EatClub's computer vision models.
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Job Post Details
Job details
Job type
- Full-time
Location
Bengaluru, Karnataka
Full job description
1 — A B O U T E ATC L U B
Tech-led food, at scale.
Founded in 2012, EatClub (formerly Box8) is a tech-enabled food delivery company building a
portfolio of much-loved consumer brands — Box8, MOJO Pizza, Itminaan Biryani, NH1 Bowls,
LeanCrust Pizza, ZAZA, and Globo Ice Creams. We serve thousands of meals every day across
Mumbai, Pune, Bengaluru, Hyderabad, Chennai, Kolkata and NCR. Our edge sits at the intersection of
taste, technology, automation and logistics — a full-stack approach that gives us complete control
from kitchen to doorstep.
0 2 — A B O U T T H E R O L E
Annotation as critical infrastructure.
This isn't a dashboard role. You'll sit at the foundation of our ML stack — establishing ground truth for
the image and video datasets that train EatClub's computer vision models. Every label you create
directly improves how our AI sees kitchens, packaging, plating, fulfilment and ops. You'll partner
closely with our Data, ML and Operations teams to push dataset quality, surface ambiguous edge
cases, and shape annotation standards as our systems scale.
We're looking for someone with sharp attention to detail, strong consistency, an ownership mindset,
and a real curiosity for how operations work on the ground.
0 3 — W H AT YO U ' L L D O
Build the ground truth our models learn from.
Annotate and validate image and video datasets with high consistency.
Partner with ML and Data teams to improve dataset quality at the source.
Create accurate, well-defined ground-truth labels for ML training.
Analyse annotation outputs and produce clean, actionable reports.
Run QA passes on annotation outputs and flag drift or ambiguity.
Assist with operational data reviews and ground-truth audits.
Identify and document operational edge cases worth escalating.
Escalate anomalies, mislabels and systemic inconsistencies early.
Maintain and refine annotation standards across the team.
Continuously improve labeling workflows, tools and SOPs.
0 4 — W H AT YO U ' L L N E E D
The fundamentals. Sharp, almost obsessive attention to detail.
Basic analytical thinking and comfort with patterns.
Working knowledge of spreadsheets and data tools.
Ability to follow detailed annotation guidelines.
High consistency and patience across repetitive workflows.
Clear written communication for QA notes and escalations.
Ownership — you finish what you start, accurately.
Curiosity — 'why is this an edge case?' as a habit.
P R E F E R R E D · B O N U S P O I N T S
CVAT LABEL STUDIO SUPERVISELY ROBOFLOW BASIC SQL EXCEL
CV WORKFLOWS AI/ML EXPOSURE
0 5 — N I C E TO H AV E
What makes you stand out.
Curiosity about how AI/ML systems are built and trained.
Process-improvement mindset — always tightening the workflow.
Exposure to CV pipelines or annotation tooling. Sharp instinct for spotting operational
inconsistencies.
Tech-led food, at scale.
Founded in 2012, EatClub (formerly Box8) is a tech-enabled food delivery company building a
portfolio of much-loved consumer brands — Box8, MOJO Pizza, Itminaan Biryani, NH1 Bowls,
LeanCrust Pizza, ZAZA, and Globo Ice Creams. We serve thousands of meals every day across
Mumbai, Pune, Bengaluru, Hyderabad, Chennai, Kolkata and NCR. Our edge sits at the intersection of
taste, technology, automation and logistics — a full-stack approach that gives us complete control
from kitchen to doorstep.
0 2 — A B O U T T H E R O L E
Annotation as critical infrastructure.
This isn't a dashboard role. You'll sit at the foundation of our ML stack — establishing ground truth for
the image and video datasets that train EatClub's computer vision models. Every label you create
directly improves how our AI sees kitchens, packaging, plating, fulfilment and ops. You'll partner
closely with our Data, ML and Operations teams to push dataset quality, surface ambiguous edge
cases, and shape annotation standards as our systems scale.
We're looking for someone with sharp attention to detail, strong consistency, an ownership mindset,
and a real curiosity for how operations work on the ground.
0 3 — W H AT YO U ' L L D O
Build the ground truth our models learn from.
Annotate and validate image and video datasets with high consistency.
Partner with ML and Data teams to improve dataset quality at the source.
Create accurate, well-defined ground-truth labels for ML training.
Analyse annotation outputs and produce clean, actionable reports.
Run QA passes on annotation outputs and flag drift or ambiguity.
Assist with operational data reviews and ground-truth audits.
Identify and document operational edge cases worth escalating.
Escalate anomalies, mislabels and systemic inconsistencies early.
Maintain and refine annotation standards across the team.
Continuously improve labeling workflows, tools and SOPs.
0 4 — W H AT YO U ' L L N E E D
The fundamentals. Sharp, almost obsessive attention to detail.
Basic analytical thinking and comfort with patterns.
Working knowledge of spreadsheets and data tools.
Ability to follow detailed annotation guidelines.
High consistency and patience across repetitive workflows.
Clear written communication for QA notes and escalations.
Ownership — you finish what you start, accurately.
Curiosity — 'why is this an edge case?' as a habit.
P R E F E R R E D · B O N U S P O I N T S
CVAT LABEL STUDIO SUPERVISELY ROBOFLOW BASIC SQL EXCEL
CV WORKFLOWS AI/ML EXPOSURE
0 5 — N I C E TO H AV E
What makes you stand out.
Curiosity about how AI/ML systems are built and trained.
Process-improvement mindset — always tightening the workflow.
Exposure to CV pipelines or annotation tooling. Sharp instinct for spotting operational
inconsistencies.
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