传感器算法工程师 Sensors Algorithms Engineer

Tesla Sensing Team is responsible for architecting, designing, validating and integrating state-of-the-art sensing technologies for all Tesla vehicles. The sensors we develop support ADAS (Autopilot), safety, passenger comfort, vehicle dynamics and other subsystems. We are looking for an Algorithms Engineer to join our dynamic team in a fast-paced environment. As a Sensors Algorithms Engineer, you will be responsible for designing, prototyping, implementing and validating algorithms for various sensors. You will work closely with platform software engineers, hardware design engineers, mechanical engineers to address issues discovered from development through deployment, understand and debug hardware and software interactions from prototyping through product launch, manage priorities and support a host of projects simultaneously.

Responsibilities

• Design and implement DSP algorithms including filtering, time, frequency-domain analysis, and feature extraction for real-time sensor applications
• Develop novel solutions with efficient implementations for real world hard and unfamiliar problems while meeting project milestones.
• Work with hardware teams on sensor signal chain design including but not limited to raw signal processing, de-noising, calibration strategies etc.
• Work backwards from feature definition and application scenarios to define sensor specifications
• Breakdown the feature definition into viable use cases to aid with the implementation and testing of the algorithm
• Modeling and simulation of system designs to demonstrate performance metrics
• Validate algorithm performance through Monte Carlo simulations, A/B testing, and field data analysis; track KPIs including detection rate, false-alarm rate, SNR, and latency
• Develop solutions with Machine Learning algorithms for applications
• Define and lead the execution of experiments and trials to collect data, for model training and validation.
• Use common industry signal processing tools such as IDL, MATLAB, Python (Pytorch) or C++ to analyze data and generate algorithms and train models.
• Work with the Platform Software engineer to optimize or implement the design on embedded platform in the production software
• Optimize algorithms for embedded platforms including fixed-point implementation, memory management, and real-time performance constraints
• Collaborate with a broad range of cross-functional teams including mechanical, hardware, software, program management, and senior leadership
• Potential for broad range of problems and need to have the willingness to learn and tackle new problems
• Define KPIs and design framework to assess the performance of the algorithms in production

Requirements

• Strong foundation in DSP fundamentals: sampling theory, Z-transform, windowing, spectral estimation, statistical signal processing, probability theory, and power spectral density estimation techniques.
• Experience with DSP KPIs (detection rate, false-alarm rate, SNR, latency, compute/memory) and validation methods (Monte Carlo, A/B testing).
• Hands-on experience with filtering and tracking algorithms (Kalman/EKF/UKF, LPF) and frequency-domain analysis (FFT/STFT/Wavelets etc.).
• Experience with sensor calibration, and HW/SW co-design.
• Experience in Machine learning algorithms architecture, data collection, model training and validation.
• Development experience in Python/C/C++/Matlab for scientific/mathematical problem solving as well as testing and data analysis
• Solid fundamentals, critical thinking, results-driven, product-oriented mindset, self-driven, and great learning capabilities
• Hands-on experience with developing an integrated system of hardware and software preferred.
• Experience with automotive sensors preferred; ability to independently own DSP-hardware integration and propose practical solutions
• High-volume product development experience required – Proven track record shipping products at scale with tight timelines and real-world deployment constraints
• Independent operation and self-driven execution – Ability to operate autonomously, own end-to-end delivery, and drive results without heavy supervision
• Failure analysis and continuous improvements – Hands-on experience with root cause analysis, debugging production failures, and implementing data-driven enhancements to boost reliability, performance, and efficiency
• Excellent written and verbal communication skills
• Proven cross-functional collaboration and leadership skills
• Penchant and proven track record of solving complex challenging problems
• Proficiency in data visualization and statistical analysis
• PhD/MS in Computer Engineering, Electrical Engineering, Physics or related fields + 2 years of industry experience
• BS in Computer Engineering, Electrical Engineering, Physics or related fields + 4 years or industry experience

This job application may involve an interview with an interviewer outside of Tesla China. If you complete your application, you agree Tesla provides your application information to overseas interviewers in Tesla, Inc. for recruitment purposes. More details and contact information please see here. (here hyperlink: https://app.mokahr.com/social-recruitment/tesla/46129#/)