Autobrains applied-research algorithm teams work on the next generation of autonomous vehicles. Autobrains technology is the “Brain Behind the Car” and is the most advanced AI platform that mimics the way our brain processes signals.

You’ll benefit from never-ending intellectual challenges as we redefine AI for ultra-scale autonomous platforms and products. On top of that, you’ll work with brilliant people in an amazing environment where professional and personal development is a top priority.

Responsibilities:

• Understand deeply, implement, and evaluate recent state-of-the-art (SOTA) algorithms in computer vision (e.g., object detection, self-supervised learning, network pruning, and quantization).
• 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).
• If algorithm adaptation does not yield sufficient accuracy, you will be expected to develop entirely new algorithms (architectures/cost functions/learning objectives) that fit our client's needs.
• Most importantly, you are expected to provide production teams with technical support in the deployment of your algorithms to the company's products.
• Innovative research does not come from “lone wolves” - you are expected to 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:

• Ph.D. in a Relevant Discipline.
• 5 Years of Research Experience in Deep Learning, Computer Vision, and Machine Learning.
• Must have published in top-tier journals or conferences on algorithms, computer vision, or deep learning.
• 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.
• Research skills: Ability to conduct independent research, stay up-to-date with the latest advancements in deep learning, and contribute to the development of new algorithms and models.
• Problem-solving skills: Ability to identify problems, evaluate alternatives, and implement effective solutions.
• Adaptability: Openness to learning new techniques, adapting to changing requirements, and embracing new technologies.
• Attention to detail: Ability to ensure accuracy and thoroughness in all aspects of research, including data collection, analysis, and presentation of results.
• Initiative: Proactive in taking on new challenges, seeking out opportunities to improve processes, and driving results.