Data Acquisition & Preparation Associate

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Posted:4 days ago| Platform: Linkedin logo

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Job Type

Full Time

Job Description

Job Title: Data Acquisition & Preparation Associate


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About Smartan:

Smartan FitTech is a deep-tech startup revolutionizing the fitness ecosystem through cutting-edge computer vision and intelligent systems. We are currently expanding our team to support the development of AI-driven fitness products and solutions.


Role Overview:

We are looking for a meticulous and tech-savvy individual to support our AI and engineering teams in data-related operations. This role focuses on managing the complete data acquisition pipeline — from raw data collection to final dataset preparation enabling high-quality inputs for machine learning and system calibration.

Important:


Key Responsibilities:

data collection

data segregation

Prepare structured datasets

Upload and organize data

camera calibration

• Coordinate with the AI and software teams to meet data format and quality requirements.

• Maintain documentation of data collection sessions, file naming conventions, and calibration logs.


Required Skills:

• Basic understanding of image/video data formats, storage structures, and annotation workflows.

• Experience or willingness to learn camera calibration and sensor setup.

• Familiarity with tools like OpenCV, Python (optional but preferred), and data transfer protocols.

• Ability to follow structured protocols and pay attention to detail.

• Good organizational and file management skills.


Preferred Qualifications:

Bachelor's degree or diploma in any field.

• Previous internship or project experience in data collection or preparation for machine learning.

• Background in Computer Science, Electronics, AI, Data Science, or related fields.

• Familiarity with computer vision pipelines is a plus.


Why Join Us?

• Opportunity to work on cutting-edge AI & computer vision systems.

• Be part of a growing startup shaping the future of intelligent fitness tech.

• Collaborative work culture with exposure to cross-functional teams.

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