Imagry is seeking a passionate Algorithms Engineer with a robust background in motion planning and decision-making across various autonomous systems. If you thrive in dynamic, team-oriented settings, we want you on our side. You are planned to be a pivotal part of our mission to pioneer the next generation of autonomous driving solutions in Haifa, Israel.

Role Insights: As a Senior Algorithms Engineer you will spearhead the creation of cutting-edge motion planning and decision-making algorithms pivotal to our autonomous driving systems' efficacy and safety. You will engage with a diverse team of experts, crafting algorithms that promote astute decision-making and seamless motion planning amidst bustling urban landscapes.

Responsibilities:

1. Lead the design and development of the behavioral layer for autonomous driving systems.
2. Research, develop, and implement advanced motion planning and decision-making algorithms, ensuring safe and efficient vehicle behavior.
3. Collaborate closely with the simulation team to validate and refine algorithms under diverse scenarios.
4. Integrate developed algorithms with other subsystems, including perception, control, and system integration.
5. Optimize algorithms for efficient execution on targeted platforms.
6. Stay informed with the latest research and advancements in autonomous motion planning and decision-making.
7. Actively participate in team's technical discussions, code reviews, and brainstorming sessions.

Qualifications:

1. MSc or Ph.D. degree in Computer Science, Electrical Engineering, Robotics, or a related field.
2. Proven experience in design and development of motion planning and decision-making algorithms for complex environments of products in production.
3. Deep understanding of mathematical concepts such as Linear algebra, Non-Linear optimization, statistical inference.
4. Proficiency in programming languages C++, Python.
5. Relevant experience in the autonomous driving industry or associated domains.
6. Excellent communication and collaboration skills.

Preferred Qualifications:

1. Hands-on experience with Reinforcement Learning-based approaches, notably MDPs, POMDPs, and other decision-making paradigms.
2. Solid grounding in vehicle dynamics and control theory.
3. Familiarity with simulation methodologies including Software-In-the-Loop (SIL) and Hardware-in-the-Loop (HIL).
4. Experience with simulation tools such as ROS (Robot Operating System) or analogous frameworks.
5. Demonstrated leadership skills in guiding technical projects or initiatives.