Deep Learning Research Engineer

An elite, high-caliber Artificial Intelligence research and algorithm powerhouse specializing in cutting-edge Computer Vision, Deep Learning, and Reinforcement Learning architectures.

Founded by renowned serial entrepreneurs with a proven history of high-profile acquisitions by global tech giants, the firm delivers deep algorithmic solutions to premier international enterprise clients.

Employing a boutique group of ~20 top-tier researchers and algorithm specialists in Israel, the company provides a deep-tech research culture tackling complex, open-ended mathematical and computational challenges.

Located in the Central region (Train Station access), operating on a hybrid work model.

Role Description-

• Serving as an Algorithm Developer / AI & Computer Vision Researcher, joining an elite research team driving end-to-end algorithmic innovation for mission-critical enterprise solutions.
• Owning the entire algorithmic research lifecycle from problem formulation and academic literature review through Proof of Concept (PoC), design, modeling, and performance evaluation.
• Conducting hands-on research and development using advanced Deep Learning, Reinforcement Learning, and Computer Vision techniques to solve complex multi-modal problems.
• Developing and implementing production-ready models in Python (and C++ where performance/optimization requires), transitioning theoretical prototypes into high-performance solutions.
• Performing comprehensive benchmark evaluations, hyperparameter optimization, and validation across diverse datasets.
• Collaborating cross-functionally with fellow top-tier algorithm developers, software architects, and tier-1 enterprise stakeholders.

Requirements-

• B.Sc. in Computer Science, Electrical Engineering, Software Engineering, Mathematics, Physics, or a related quantitative discipline – Mandatory (Advanced degree M.Sc. / Ph.D. – Advantage)
• 3+ years of hands-on experience in Algorithm Development / Applied AI Research – Mandatory
• Deep, proven hands-on expertise with Deep Learning architectures and frameworks (e.g., PyTorch, TensorFlow) – Mandatory
• Strong foundational background in Computer Vision, Machine Learning, or Digital Signal Processing (DSP) – Mandatory
• Deep proficiency in Python for algorithm design, model training, and data manipulation – Mandatory
• Hands-on experience with Reinforcement Learning (RL) – Significant Advantage
• Programming experience in C / C++ for performance-critical components – Advantage
• Strong mathematical orientation, analytical depth, and ability to tackle open-ended research challenges independently – Mandatory