Software Engineer - Machine Learning (SDV), POWER
Core
Design, train, and deploy machine learning models for resource-constrained edge hardware in automotive powertrain systems.
Role type
Machine Learning Engineer (Edge/Embedded)
Builds
Real-time ML estimators and inference logic for powertrain control units.
Domain
Automotive / Embedded Systems / Edge AI
Deliverable
production ML models
Required skills
Feature engineering, statistical modeling, hyperparameter tuning, model inference optimization, C programming, C++ programming, Python programming, embedded hardware interfacing, signal processing, model quantization, model pruning, time-series data analysis
Preferred skills
TensorFlow Lite for Microcontrollers, SciKit Learn, Raspberry Pi hardware expertise, Linux/Raspbian OS customization
Technologies
C, C++, Python, TensorFlow Lite, SciKit Learn, Linux, Raspbian, GPIO, SPI, Kalman filters
Responsibilities
Design and train ML models for edge hardware; perform feature engineering on sensor datasets; optimize model inference for real-time execution; develop real-time application logic in C/C++; interface with hardware platforms like Raspberry Pi; validate ML models against real hardware or simulators.
Seniority
Mid-level, hands-on IC
