Remote Part-Time ML & AI Engineer for Robotics

ROZOR; Qatar; On-site; QAR 223,000 - 446,000; Part time

Job summary

ROZOR is seeking a remote, part-time AI team member to design, train, and optimize perception models powering ROZOR robots with robotics data to build algorithms for environmental awareness across object detection, semantic segmentation, behavior prediction, and multi-modal fusion.

You will train models for detection, segmentation, tracking, or classification, build data pipelines with multi-modal sensor data, and integrate ML models into robot systems while optimizing inference on embedded

Qualifications

• Bachelor's/Master's degree (or current student) in Computer Science, AI, Robotics, or related field.
• Strong foundation in machine learning and deep learning.
• Proficiency in Python, PyTorch or TensorFlow.
• Experience with detection, segmentation, tracking, or classification models.
• Hands-on experience with image or point-cloud datasets.
• Familiarity with OpenCV, NumPy, and ML tooling.
• Strong debugging and experiment evaluation capabilities.
• Ability to work independently in a fast-moving robotics environment.

Responsibilities

• Train deep learning models for object detection, tracking, and classification.
• Develop semantic segmentation and mapping models.
• Build behavior and motion prediction models.
• Build data pipelines and work with multi-modal sensor data.
• Integrate ML models into robot systems.
• Optimize inference performance on embedded compute.
• Validate through testing and collaborate with perception and autonomy teams.

Skills

Python

PyTorch

TensorFlow

OpenCV

NumPy

ML tooling

Debugging

Experiment evaluation

Education

Bachelor's/Master's degree (or student) in CS/AI/Robotics

Tools

None

Job description

ROZOR is seeking a remote, part-time AI team member to design, train, and optimize perception models powering ROZOR robots with robotics data to build algorithms for environmental awareness across object detection, semantic segmentation, behavior prediction, and multi-modal fusion.

You will train models for detection, segmentation, tracking, or classification, build data pipelines with multi-modal sensor data, and integrate ML models into robot systems while optimizing inference on embedded