Senior Algorithms Engineer - Battery Diagnostics and Prognostics

Description
Job Description
GM Israel takes a significant part in transforming traditional cars into software-defined vehicles. We shape the face of the future vehicles in diverse fields by developing cutting edge technologies.
GM is committed to Zero Emission, Zero Crashes and Zero Congestion vision.
About the Group:
TRP Diagnostics and Prognostics - ALGOLiON group focus is developing and releasing the Earliest warning battery hazard detection and prevention software . The group uses ALGOLiON (formerly Israel-based battery software startup and today integral part of GM-Israel) novel algorithms which take data streams from battery management systems to identify anomalies in battery cell performance that may impact the performance of a battery pack or the safety of a vehicle.
About the role:
We are looking for an algorithm engineer who will design and develop algorithms in the field of battery warning and hazard detection.
What will you do:

• Join a diverse team that combines expertise from various domains to develop advanced anomaly detection algorithms for detecting battery hazards.
• Examine, design, develop, and implement new algorithmic approaches and techniques in both electrical vehicles and manufacturing lines, ensuring seamless integration and real-time performance.
• Optimize existing algorithms to improve performance and scalability.
• Provide end-to-end algorithmic solution together with SW teams from idea to released SW. This includes simulating, testing, and validating the algorithms performance with real data.
• Work with global teams with experts in the field of batteries.
• Keep safety a priority and improve safety of GM electric vehicles in the field of electric batteries.

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Additional Description
Your Skills & Abilities (Required Qualifications):

• Bachelor's or higher degree in Electrical andor Computer Engineering, Physics, or a related field.
• At least 5 years practical experience and at least 3 of them in designing and developing algorithms including implementation to software within the areas of signal processing, real time data analysis, and machine learning.
• Proficiency in Python, Scikit-learn and either PyTorch or TensorFlow.
• Capability to propose research directions, train classifiers, and identify patterns from a big data environment consisting of time series and tabular data.
• A passion for solving physical problems using both machine learning and traditional algorithm development.
• System understanding - seeing the overall picture and applying solutions.
• Self-fast-learner, responsible, great communicational skills, team player, and details-driven character.
• Excellent English skill both written and verbally.

Preferred Qualifications:

• Familiarity with battery electrochemistry, power engineering and/or batteries management concepts - big advantage.
• M.Sc./PhD.

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