Junior Computer Vision and AI Engineer (Munich/Remote)

MESASIGHT GmbH
München, Germany
24 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Shift work
Languages
English, German
Experience level
Junior

Job location

Remote
München, Germany

Tech stack

Clean Code Principles
Artificial Intelligence
Computer Vision
BASIC (Programming Language)
Software Design Patterns
Python
Machine Learning
NumPy
Object-Oriented Software Development
Software Engineering
PyTorch
Large Language Models
Deep Learning
Generative AI
Pandas
Scikit Learn
Information Technology

Requirements

Do you have experience in Software development?, Do you have a Master's degree?, * A Bachelor's or Master's degree in Computer Science or a related technical field

  • Very good experience in Python functional and object-oriented programming
  • Knowledge of software development using clean code and design principles, and basic of design patterns
  • Hands-on experience with machine learning, deep learning, and computer vision
  • Proficiency in libraries like PyTorch, Scikit-learn, Pandas, and NumPy
  • Fluency in English, * Working experience in computer vision using deep learning methods
  • Basic knowledge in Generative AI and Large-Language Models (LLMs)
  • Fluent in German

Benefits & conditions

  • The position is available as full-time (35-40 hours per week)
  • Flexible working hours and the option to work fully-remote, hybrid (remote/in-office), or completely in-office at our location at the Munich Technology Center
  • Be part of a small and highly motivated team, where everyone has a huge passion for technology and pushing the boundaries of what is possible

About the company

MESASIGHT was founded in October 2020 in Munich to deliver cutting-edge image analysis solutions to customers in the areas of public security. Our focus and expertise lie in research and development of high-performance deep learning solutions. We look forward to expanding our team and building new AI solutions for challenging problems in computer vision.

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