Develop Rule-Based prediction and ego-vehicle path planning models for assisted and automated driving domain
• Translate technical ideas into algorithms
• Review and consolidate existing code and ability to enhance it and reuse it
• Work with large amounts of real and simulation data to improve algorithmic performance
• Create Key Performance Indicators to support validation and verification of algorithms developed both in-house and by suppliers
• Lead the Verification and Validation plans for evaluation of the both JLR and supplier algorithms
• Optimize algorithms for Embedded applications
• Contribute towards algorithm specification, FMEAS, robustness disciplines and design validation plans
• Perform code reviews to ensure implementation is in line with architecture
• Planning and Scheduling: Agree a complete end to end development schedule for software including release. Timing targets, capable of delivering activities to achieve these plans and the drafting / evaluation of software release notes.
• Teamwork and Leadership: Positive team player, with the strength of character to drive non expert software engineers and mechanical engineers to support the development of robust code.
• Understanding the business: Understands team & group goals
• Coach, Train & Mentor: Shares knowledge with others through regular training and delivery support is fundamental to this role also.
Experience with state of art planning and prediction models
• Experience with complex mathematical models and optimization algorithms
• Experience with benchmarking and performance optimization of complex systems
• Experience with robotics simulation environments
• Understanding of risk-aware concepts in intention prediction and path planning algorithms and general uncertainty management
• Experience with programming languages like Python and C++
• Experience with data pre-processing for tuning and testing complex Neural networks
• Strong mathematical reasoning skills
• Experience with continuous integration principles for software development
• Fundamental knowledge of electronic hardware systems
• A bachelor's degree or equivalent experience
• Version control
Preferred:
• MS or Ph.D in the areas of Mathematics, Automotive Engineering, Mechanical Engineering, Robotics, or other related fields
• Experience in one or more of the following
• Vehicle Prediction
• Pedestrian/Bicycle prediction
• Ego Vehicle Path planning
• Vehicle Motion Control
• Experience with ML frameworks such as Pytorch or TensorFlow
• Experience in developing complex algorithms in C++ & Python skills (C++11 or newer)
• Knowledge of automotive Functional Safety concepts