Mentee Robotics is redefining humanoid automation with an AI-first approach, integrating cutting-edge perception, reasoning, and dexterous manipulation into a fully autonomous humanoid robot that continuously adapts and learns. Our flagship product, Menteebot v3, is designed to seamlessly integrate into industrial, logistics, and retail environments, performing complex tasks with human-like adaptability.

We are looking for an experienced Senior Software Engineer to join our AI Platform team. This role is central to our "data-focused" strategy. You will build the core data infrastructure that fuels our AI-first approach, responsible for the entire lifecycle of our robotics data.

Responsibilities

• :Design and implement high-performance, scalable software solutions, primarily using Python
• .Design and build robust, scalable ETL pipelines to ingest and transform multi-modal robotics data, including video, sensor streams (joint states), teleoperation logs, and open-source datasets
• .Architect and maintain our core data lake infrastructure (e.g., S3), creating a "single source of truth" for tagged and versioned robotics data
• .Work closely with AI researchers to define labeling schemas, ensure data quality
• ,Champion best practices in data engineering and software development within a cutting-edge robotics environment

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Requirement

• s:
  5+ years of experience as a Software Engineer, Data Engineer, or ML Infrastructure Engine
• er.Extensive experience and strong proficiency in Python – a must-ha
• ve.Deep understanding and hands-on experience with ETL and data pipeline development – a must-ha
• ve.Proven experience working with data lake technologies (e.g., S
• 3).Experience with cloud platforms (e.g., AWS, GCP, Azur
• e).Solid understanding of database systems (SQL/NoSQ

L).
Advanta

• ges:
  Familiarity with robotics data (e.g., ROS bags, sensor time-series) or multi-modal data (video, text, sensor fus
• ion).Experience with data annotation/labeling platforms (e.g., Label Studio, V7, or custom-built to
• ols).A strong understanding of the data-centric challenges in modern AI (e.g., active learning, data curation for foundation mod
• els).Familiarity with containerization and orchestration (Docker, Kuberne
• tes).Experience with stream processing technologies (e.g., Ka
• fka).Deep understanding of L