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