42dot
Machine Learning & Data Engineer, Vehicle Modeling
About this role
42dot seeks a Machine Learning & Data Engineer to build ML-driven vehicle modeling systems that combine physics-based approaches with real-world fleet data. You'll develop scalable cloud infrastructure for model calibration, parameter estimation, and hybrid data-physics modeling to improve vehicle intelligence and autonomous driving capabilities.
What you'll do
- Develop ML and hybrid physics-data methods to improve vehicle and component model accuracy
- Create calibration and parameter estimation techniques across varying vehicle states and operating conditions
- Build scalable workflows to compare model predictions against test, simulation, and real-world data
- Design pipelines for ingesting, cleaning, synchronizing, and processing large-scale vehicle telemetry and time-series data
- Develop cloud-based infrastructure for data processing, model training, simulation, and validation
- Build tools for dataset management, model evaluation, experiment tracking, and reproducible development
What they're looking for
- Machine learning and statistical modeling
- Python or equivalent data engineering languages
- Cloud platforms and distributed data processing
- Time-series data analysis and vehicle telemetry
- Model calibration and parameter estimation
- Data pipeline design and ETL workflows
- Physics-informed machine learning
- SQL and data storage systems
Opens the application — the Jobs AI extension fills it for you. Set up autofill
Opens the official application on the employer’s site. No login required.
42dot
42dot develops software-defined vehicle technology for next-generation in-vehicle infotainment, autonomous driving systems, and digital cockpits, with a focus on Linux-based applications, 3D visualization, and Android Automotive OS. The company is hiring embedded software engineers, Android engineers, and senior/staff software engineers to architect real-time systems, optimize graphics performance, and build safety-conscious user interfaces for Hyundai Motor Group's vehicles.
- Website
- 42dot.ai
Likely interview questions
- Describe your experience combining physics-based models with machine learning to improve predictions—what was your approach and what challenges did you face?
- Walk us through how you would design a data pipeline to ingest, clean, and synchronize large-scale vehicle telemetry from multiple sources.