AI Researcher

Location:

(00193) Italy

Salary:

market rate

Type:

Permanent

Main Industry:

Search Information Technology Jobs

Advertiser:

microTECH Global Ltd

Job ID:

131771517

Posted On: 

07 April 2025

About the company:

This company operates at the forefront of computer vision and deep learning technologies, offering transformative solutions for a variety of industries. Their projects empower clients to leverage spatial intelligence and advanced 3D modeling for applications ranging from robotics to augmented reality, all while fostering a collaborative, innovative, and research-driven work environment.

Commitments:

Problem-solving: This company develops advanced algorithms focused on 3D reconstruction and dense depth estimation, applying creative deep learning solutions for industries like robotics and autonomous vehicles.
Team participation: Collaboration is key, with regular updates, scientific documentation, and presentations to ensure knowledge is shared and the team stays aligned on project goals.
Research: Employees contribute to research publications and present at conferences, helping shape the future of computer vision and machine learning.
Management and deployment: From development to deployment, the company manages the full lifecycle of projects, ensuring continuous improvement and optimization of solutions.

Required Qualifications:

Master’s degree in computer science, computer engineering, data science, mathematics, or a related field.
At least one year of experience in deep learning-based dense depth estimation and 3D reconstruction, and three years in SLAM and 3D reconstruction.
Proficiency in Python and libraries like SciPy, NumPy, OpenCV, TensorFlow/Keras, and PyTorch.
Strong mathematical and problem-solving abilities, with excellent technical writing and communication skills.
Ability to work effectively in a collaborative environment.

Preferred Qualifications:

Background in mathematics, geometry, statistics, and machine learning fundamentals.
Familiarity with machine learning paradigms such as self-supervised, unsupervised, and supervised learning.
Knowledge of deep learning-based 3D models, SLAM, monocular depth estimation, point clouds, and camera parameter estimation.

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