Autobrains is the leading Israeli AI company developing automated driving products and capabilities. The technology is based on a fundamental paradigm shift from a traditional deep-learning approach to a biologically plausible self-learning AI.

The technology is protected by over 250 patents and adopted by multiple leading automotive players. Autobrains technology solves several key gaps on the way to full, safe and scalable autonomous driving.

Autobrains is backed by top investors and key players in the automotive industry such as Temasek, Toyota, BMW, Continental, Vinfast, and Knorr-Bremse, with headquarters at the heart of Tel Aviv.

Responsibilities:

• Understand deeply, implement, and evaluate recent state-of-the-art algorithms in computer vision (e.g., object detection, self-supervised learning, network pruning, and quantization).
• Provide production teams with technical support in the deployment of your algorithms to the company's products.
• Adapt state-of-the-art algorithms to our specific domain (automotive), our specific constraints (low compute edge devices, real-time needs), and our data regime (small number of annotated images and infinite amount of unlabeled data, video sequences).
• Design new algorithms (architectures/cost functions/learning objectives) that fit our client's needs.
• Be a team player: collaborate well with others, clearly communicate your results, and align your work with the team's goals, while maintaining your self-sufficiency
  
  

Requirements:

• MSc.in relevant disciplines (e.g., EE/CS/Applied Math/Physics) - Must
• 5 + years of industry experience in research positions in Deep Learning, Computer Vision, and Machine Learning.
• Experience with self-supervised learning is an advantage
• Experience with active learning is an advantage
• Availability for a full-time position from our office HQ in Tel-Aviv
  
  

Attributes:

• Technical expertise: Strong knowledge of deep learning techniques, computer vision, machine learning, and related fields, as well as experience with deep learning frameworks such as TensorFlow, PyTorch, etc.
• Strong analytical skills ranging outside the realm of deep-learning - e.g. probability theory, optimization theory.
• Problem-solving skills: Ability to identify problems, evaluate alternatives, and implement effective solutions.
• Proactive in taking on new challenges, seeking out opportunities to improve processes, and driving results
• Good inter-personal skills both in day-to-day interaction for achieving team development goals, and in communicating ideas inside / outside the team.