Requirements:
M.Sc. or PhD. in Computer Science, Mathematics, Engineering or a related field
6+ years of hands on experience with coding Deep learning / Machine learning / Reinforcement-learning / Statistical modeling based solutions
4+ years Experience modeling auction dynamics in first-price environments (bid shading, market price modeling, win-rate prediction, clearing-price / floor-price estimation)
Strong knowledge in Python
Good knowledge in Java, Scala or C#
Experience in data analysis and visualization and strong knowledge in SQL
Possess strong problem solving and critical thinking skills
Bonus points if you have:
Deep understanding of RTB ecosystems and standards (OpenRTB), header bidding (Prebid client/server), and ad-exchange integrations
Hands-on experience with budgeting/pacing, frequency capping, throttling, and guardrails to meet margin/CPA/ROAS targets
Strong grasp of measurement and calibration (CTR/CVR calibration, eCPM modeling, lift studies) and experimentation (A/B tests, multi-armed bandits)
Experience in developing models using deep learning techniques and tools
Experience in developing software within a distributed computation framework.

Requirements:
M.Sc. in Computer Science / Electrical Engineering from top-notch universities.
At least 6 years of hands-on experience in deep learning, computer vision, and machine learning in Python.
Experience in writing highly optimized, scalable and reliable code.
Experience in writing real-time code for a target hardware - Advantage
Strong knowledge of computer vision techniques, including object detection and semantic segmentation- Advantage.
Availability for a full-time position from our office HQ in Tel-Aviv.
Attributes:
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. Advantage - Publications in top-tier journals or conferences of computer vision or deep learning.
Team player: Collaborate with others, clearly communicate your results, and align your work with the team's goals, while maintaining your self-sufficiency.
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.
Initiative: Proactive in taking on new challenges, seeking out opportunities to improve processes, and driving results.
Results-driven: We are looking for someone who is driven by results and has a strong work ethic.

Requirements:
B.Sc. in Computer Science / Software engineering / Mathematics / similar field
Minimum of 5 years of hands-on industry experience in backend development (Python)
Experience in Devops in cloud infrastructure (Kubernetes etc.) - significant advantage
M.Sc. in Computer Science / Software Engineering / similar field - significant advantage
Experience in architecture and maintaining cloud systems - significant advantage
Have a solid background in software engineering methodologies, such as git & CI/CD
Fast learner: you can quickly master concepts, disciplines and methods
Team player: you work well with people, as well as by yourself
Pragmatic: you know how to deconstruct a problem into few smaller problems
Concise: you get stuff done, in a simple, elegant way.

Requirements:
M.Sc./PhD Computer Science / Mathematics / Physics or similar
Significant academic research experience in relevant fields.
Extensive knowledge of algorithms, with a focus on graph theory and combinatorial optimization.
5+ years of hands‑on experience designing, developing and deploying production‑grade algorithms-must.
Analytical: you can extract the essential features of a complex real-life problem to arrive at a simple and relevant mathematical model.
Experience in Python programming - Advantage.
Fast learner: you can quickly master concepts, disciplines and methods.
Strong interpersonal and communications skills.
Hands-on: you are able to realize your ideas in code.

Requirements:
B.Sc. in Electrical Engineering - MUST
5+ years experience in algorithm development, preferably in complex, data-intensive environments
Deep expertise in Python, including statistical and machine learning packages
Proven experience across all algorithm development phases: research, implementation, testing, deployment, and debugging Familiarity with testing frameworks (e.g., unit tests, E2E tests, performance and memory profiling)
Intensive usage of AI coding tools like Cursor or equivalent (e.g., GitHub Copilot, CodeWhisperer)
Advantage
M.Sc. or higher in Electrical Engineering, Computer Science, or a related field
Prior experience with:
HW/SW integration or ATE/Chip testing
Version control systems (e.g., Git) and CI/CD tools
Distributed compute frameworks (e.g., Spark, MLRun)
Containerization and cloud orchestration (e.g., Kubernetes, cloud APIs)
Business intelligence tools (e.g., Tableau or equivalent)
AI platforms and agents that interface with model training, data annotation, performance monitoring, or autonomous debugging
Familiarity with chip production or design methodologies.

Requirements:
5+ years of experience in autonomous driving / robotics / motion planning / navigation / real-time systems
Strong expertise in Path Planning and/or optimization-based planning methods
Strong C++ skills (Python is a plus)
Experience working with real-time systems and performance-critical code
Strong problem-solving skills, end-to-end ownership, and ability to work independently
Experience in automotive production environments.

Requirements:
Detailed understanding of imaging systems & module designs (image sensors, optics, mechanics, auto-focus, optical image stabilization, assembly processes, etc).
Familiarity with image signal processing pipelines.
Working knowledge of imaging system simulations and evaluation of simulation results.
Good understanding of image quality metrics and image quality evaluation.
Expertise in system level modeling/simulation, data analysis, and image/signal processing in Matlab and/or Python.
Experience defining performance specification in from system level, through sub-module and competent.