Senior AI/ML Process Engineer - Body Assembly

Rivian; Normal (IL); On-site; USD 99,000 - 123,000; Full time

Job summary

Rivian Automotive seeks an innovative engineer to blend AI/ML with manufacturing excellence in the Body Assembly area at the Normal, IL facility. You will drive digital transformation by developing AI-powered solutions that enhance quality and equipment performance.

The role reports to the Process Engineering Manager and requires shift flexibility to support operations. Collaboration with IT, quality and plant teams will deliver robust models and actionable insights.

Qualifications

• Bachelor's degree in a relevant engineering or data science field.
• 3-5+ years in a process/manufacturing engineering role applying ML or advanced statistics.
• Experience with Python or R and time-series data platforms.

Responsibilities

• Apply process engineering and ML/AI methods to analyze manufacturing data (End of line, sensor, press data).
• Develop and deploy predictive models for yield, throughput, and downtime.
• Build data pipelines and work with MES data for model training and deployment.
• Design, train, validate, and deploy ML models for real-time process control and quality prediction.
• Present findings clearly to technical and non-technical stakeholders.

Skills

Python

R

SQL

Time-series databases

Databricks

ML algorithms

Statistical analysis

Education

Bachelor's degree in Electrical Engineering

Computer Engineering

Computer Science

Data Science

Statistics or related engineering degree

Tools

OSIsoft PI

InfluxDB

Azure

AWS

GCP

AutoCAD

CATIA/ENOVIA

DOE

PFMEA

MTM/MODAPTS

Job description

Rivian Automotive seeks an innovative engineer to blend AI/ML with manufacturing excellence in the Body Assembly area at the Normal, IL facility. You will drive digital transformation by developing AI-powered solutions that enhance quality and equipment performance.

The role reports to the Process Engineering Manager and requires shift flexibility to support operations. Collaboration with IT, quality and plant teams will deliver robust models and actionable insights.