DeepCube, the AI Division of Nano Dimension Ltd. (NNDM), is an integral component of its parent company, located in the center of Tel Aviv, near ‘Tel Aviv-Hashalom’ train station.

We serve as trailblazers in the realm of artificial intelligence, focused on elevating industrial processes through sophisticated and innovative AI solutions. Our dedicated team is committed to driving excellence in the development and implementation of end-to-end predictive analytics projects.

Utilizing large scales of customer’s data, our mission is to empower industries with intelligent solutions that strategically enhance efficiency, optimize performance, and introduce transformative advancements. Our unwavering commitment to technological advancement fuels our ability to create comprehensive on-premises solutions, seamlessly integrating data collection, artificial intelligence, deployment strategies, and analytical dashboards.

As an applied ML/DL researcher, you will conduct research projects to advance the scientific front of AI. Your work will be done both solo and in collaboration with other deep learning engineers and researchers. We are looking for someone who is versatile, displays leadership qualities, and is passionate about taking on new challenges.

Responsibilities:

• Conduct advanced research in machine learning and deep learning, with a primary focus on time series data analysis.
• Develop and implement novel algorithms and models for time series forecasting, anomaly detection, and pattern recognition.
• Design and conduct experiments to evaluate the performance of models, iterating and optimizing as needed.
• Contribute to DeepCube’s research efforts, leading to components that will be integrated and deployed in the DeepCube product.
  
  

Requirements:

• M.Sc. in computer science or a similar technical field.
• 3+ years experience in industrial settings.
• Excellent team player with strong communication skills.
• Proficiency in Python, and experience with machine learning libraries/frameworks (e.g., PyTorch).
  
  

Preferred qualifications:

• Past working experience in development – major advantage.
• Past working experience with time series data.
• Publication in a top-tier machine or deep learning peer-reviewed venue.