Project Cursa - Robot Manipulation Video Annotator

Round 1: Online aptitude / logical reasoning test → Round 2: Annotation task and style‑guide assessment → Round 3: HR interview (fit, availability and compensation discussion)

Welo Data promotes a collaborative, results‑driven culture where autonomy is balanced with regular check‑ins. Employees enjoy flexible working hours, opportunities to upskill through internal workshops, and a clear path for growth within the data and robotics domains.

Candidates typically face a three‑stage process: an online aptitude test, a practical annotation exercise where they label a short video segment, and a final HR conversation focusing on communication skills and cultural fit. The difficulty is moderate; the aptitude test evaluates basic reasoning, while the annotation task checks attention to detail and adherence to guidelines. Preparing with structured labeling practice and clear English writing will boost confidence.

Graduates (any discipline) with a minimum of 60% aggregate in the final year. Candidates from the 2024, 2025 or 2026 batch are preferred. No active backlogs at the time of joining. Strong command of written English is mandatory.

Welo Data is an emerging AI‑driven data solutions company that focuses on building high‑quality training datasets for robotics, computer vision and natural language processing. Founded by a team of robotics engineers and data scientists, the firm has quickly become a trusted partner for global robotics manufacturers looking to accelerate the learning curve of their autonomous systems. With a culture that blends technical rigor with creative problem‑solving, Welo Data encourages its employees to experiment, iterate and deliver data that powers the next generation of intelligent machines. The role of AI Video Annotator is a cornerstone of Welo Data’s Project Cursa, a flagship initiative aimed at creating richly annotated video corpora for robot manipulation tasks. As an annotator, you will be the eyes and voice of the dataset, translating raw robot footage into structured, natural‑language descriptions that feed directly into machine‑learning pipelines. This position is fully remote, allowing you to work from anywhere in India, the Philippines, Mexico or Egypt, while collaborating with a globally distributed team of data curators, robotics engineers and AI researchers. **Key Responsibilities** 1. Watch short robot manipulation videos captured from three synchronized camera angles (overhead and two wrist‑mounted views). 2. Segment each video into atomic motions, skills/sub‑tasks, and overall tasks, ensuring every second is labeled at two or more levels. 3. Write clear, concise, natural‑language descriptions for each segment, adhering strictly to a detailed style guide. 4. Accurately capture both successful actions and failures (e.g., dropped objects, missed grasps). 5. Cross‑reference all camera angles to verify object identities, contact points and spatial relationships. 6. Apply consistent vocabulary for actions, spatial terms (left/right, above/below) and object parts (handle, edge, lid). 7. Participate in periodic calibration sessions to align labeling quality with the team and client expectations. 8. Provide feedback on the style guide and suggest improvements based on edge‑case scenarios. 9. Maintain a high level of productivity while working independently, meeting daily and weekly annotation targets. 10. Use annotation tools such as Label Studio to upload, edit and export labeled data. **Tech Stack & Tools**: Label Studio (or equivalent), Google Drive for video sharing, Excel/Google Sheets for tracking, basic familiarity with robotics terminology. **Growth Path**: Starting as a freelance annotator, high performers can progress to Senior Annotator, Quality Lead, or even transition into Data Engineering or Robotics QA roles within Welo Data’s expanding product teams. **Why Join Welo Data?** You will contribute directly to cutting‑edge robotics research, gain exposure to AI data pipelines, and develop a niche skill set in video annotation that is in high demand across the AI industry. The flexible remote setup, competitive hourly pay, and a supportive community of data experts make this an ideal entry‑point for fresh graduates eager to build a career in AI‑enabled data engineering.