The Role
As a Machine Learning Engineer – Edge AI & Computer Vision, you will play a pivotal role in developing intelligent systems that operate efficiently on edge devices. You will be responsible for bridging the gap between cutting-edge research and real-world deployment, ensuring that models are not only accurate, but also optimized for performance, scalability, and resource constraints.
This role requires a deep understanding of machine learning, computer vision, and systems engineering, along with the ability to work independently and collaboratively in a fast-paced, agile environment. You will be expected to contribute across the entire ML lifecycle—from ideation and experimentation to deployment and maintenance—while maintaining high standards of code and model quality.
You will also be a key contributor to the team’s technical strategy, helping shape the future of edge AI solutions within the organization. Your work will directly impact product capabilities, user experience, and the scalability of AI systems across various platforms.
What you’ll do

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• Owns and maintains major components and complex features of a project.
  
• Drives research initiatives and develops innovative algorithms.
  
• Implements advanced algorithms with awareness of tradeoffs.
  
• Coaches team members on ML concepts, best practices, and procedures.
  
• Occasionally collaborates cross-functionally on high-impact projects to integrate AI technologies into products and services
  
• Demonstrates a strong understanding of how components and features impact the business, and ensures work is aligned with overall project outcomes.
  
• Stay updated on the latest AI trends
  
• Write and review research reports and experiment results.
  

Collaborating with

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• Data Engineering team, DevOps team, Product Management team, Engineering team.
  

Profile and Skills

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• 2-3 years of programming experience in Python
  
• Familiar with some of computer vision, machine learning and deep learning libraries (e.g. OpenCV, TensorFlow, Keras, PyTorch, Scikit-learn…).
  
• Deep understanding of ML/AI architectures and applications.
  
• Strong in experimentation, scalability, and real-time systems.
  
• Advanced problem-solving and engineering judgment.
  
• Understands the latest innovations in machine learning and computer vision
  
• Ability to design complex experiments and to communicate them clearly to other team members.
  
• Ability to design and develop components addressing the needs their research identified.
  
• Implement algorithms and solutions presented in papers.
  
• Advance projects to production (from prototype/research phase to production phase)
  
• Possesses advanced engineering skills.
  
• Strong analytical skills, able to identify trends and make decisions based on data.
  
• Knowledge of statistics and data analytics.
  

Additional Skills

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• Solid understanding of classical computer vision algorithms and concepts.
  
• Familiarity with machine vision and neural network models.
  
• Experience in developing or optimizing real-time systems.
  
• Hands-on experience with MLOps tools and workflows.
  
• Proficiency in video streaming, processing, decoding, and format handling.
  
• Knowledge of hardware and resource optimization techniques.
  
• Experience with deploying models on specialized or embedded/edge devices.
  
• Familiarity with major cloud platforms.
  

Benefits

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  Performance bonus
  
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  Medical subscription
  
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  Dental subscription
  
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  Extra days off
  
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  Flexible work schedule
  
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  Meal vouchers
  
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  Holiday vouchers