Data Labelling and QA Specialist (Computer Vision) at Aftershoot

New Delhi, delhi, India -

Full Time

Start Date

Immediate

Expiry Date

22 Apr, 26

Salary

0.0

Posted On

22 Jan, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Labelling, Quality Assurance, Image Quality, Photography, Attention to Detail, Data Annotation, Collaboration, Feedback, Machine Learning, Culling Workflows, Documentation, Visual Data, Guideline Improvement, Vendor Management, Structured Data, Edge Case Identification

Industry

Software Development

Description

At Aftershoot, we’re building a global community of photographers who spend less time behind their screens and more time behind the lens. Every feature we create, every update we ship, is designed to make post-processing easier, faster, and smarter for photographers around the world. From culling to editing to retouching. Our AI tools do all the heavy lifting, so photographers can focus on what they do best: capturing moments, telling stories, and creating magic. We’re a fast-growing, passionate team backed over 100K+ active users globally. Double-digit ARR in less than 4 years, amazing investors and team who truly believe in our mission. Our mission is clear: Become the default companion for every photographer in the world. If you care deeply about building meaningful products, working with curious and driven teammates, and being part of a team that genuinely loves what they do, we’d love to meet you. Let’s create the future of AI in photography, together. About the Role This role sits at the heart of how our AI learns. You will own how training and test data is labelled, validated, and structured for multiple culling-related use cases. A big part of your work will involve collaborating closely with external labelling vendors, reviewing their output, improving quality standards, and making sure our datasets are reliable, consistent, and scalable. If you have a strong eye for photography, understand image quality intuitively, and enjoy bringing structure and rigour to visual data, this role is for you. 💼 What you’ll do: Labelling image data for different culling use cases such as blur detection, closed eyes, and selection quality Validating and performing QA on data labelled by external vendors Working closely with vendors to iterate on guidelines and continuously improve label quality acrosstraining and test datasets Defining and maintaining clear labelling standards and documentation Ensuring datasets and labels are stored and maintained in well defined, consistent structures Flagging edge cases, inconsistencies, and gaps in data that could impact model performance Collaborating with ML and product teams to align labelling outputs with real product needs 🫂What You’ll Bring Professional photography experience is highly preferred Strong understanding of image quality, focus, expressions, and real world photography workflows High attention to detail and comfort working with large volumes of visual data Experience with data annotation, QA, or labelling workflows is a plus Ability to give clear, actionable feedback to vendors and partners Comfortable working from the Delhi office on a full time basis ⭐ What You’ll Gain Hands-on experience building growth marketing strategies in a real startup. Exposure to data analytics and campaign execution across paid and organic channels. Mentorship from experienced growth professionals. Opportunity to contribute measurable impact to company growth success. Prior experience working with computer vision or ML teams Familiarity with culling workflows used by photographers Experience creating or improving annotation guideline What happens after you apply? Step 1: If your profile aligns with our vibe and requirements for the role, our people team will reach out to you for a brief phone call. Step 2: If everything aligns, your next chat will be with one of your future team members to better understand the role and your experience. Step 3: You will then be given a task - this helps us evaluate your thought process and help you showcase your expertise. Step 4: If everything goes well, you will meet the leadership for a quick bar-raiser round. Step 5: If you do manage to clear all rounds, this is the point we make an offer, shake hands, and welcome you to the team.

Responsibilities

The role involves labelling image data for various culling use cases and validating data labelled by external vendors. Additionally, the specialist will collaborate with vendors to improve label quality and ensure datasets are reliable and consistent.