Machine learning Data Engineering

Role Summary

We are seeking a highly skilled Lead AI/ML Engineer to develop scalable machine learning solutions for large-scale automotive and engineering data. The role focuses on time-series analytics, signal processing, anomaly detection, behavioral modeling, and AI-driven insights from TB-scale measurement data.

Key Responsibilities

• Develop AI/ML solutions for large-scale time-series and vehicle measurement data.
• Build data pipelines for MDF4, ASAM, and DLT data parsing and processing at TB scale.
• Design and implement feature extraction, signal alignment, resampling, and preprocessing frameworks.
• Develop machine learning models for pattern recognition, anomaly detection, clustering, and behavioral segmentation .
• Apply supervised and unsupervised learning techniques to complex engineering datasets.
• Optimize model performance through precision/recall tuning and validation against sparse ground truth data.
• Ensure data quality, lineage, traceability, and governance across AI/ML workflows.
• Work closely with data architects, software engineers, and domain experts to deliver production-ready solutions.

Required Skills

• Machine Learning & Artificial Intelligence
• Python, PySpark
• Time-Series Analytics
• Feature Engineering & Signal Processing
• Pattern Recognition & Template Matching
• Anomaly Detection
• Clustering & Behavioral Segmentation
• Supervised & Unsupervised Learning
• Data Quality & Data Lineage
• Large-Scale Data Processing (TB+ datasets)
• Automotive Measurement Data Analysis