AI/ML Battery Manufacturing Integration Tech (Hybrid)

Ford; Kentucky; Hybrid; USD 133,000 - 251,000; Full time

Benefits offered by this job

Medical, dental, vision coverage

Vehicle discount program

Tuition assistance

Paid time off and holidays

Backup child care

Job summary

Ford Energy is seeking a data and analytics-driven engineer to drive continuous improvement on yield, scrap, quality, and throughput. You will partner with central technologists to build and deploy models on plant data, then turn outputs into actionable parameter changes and standard work.

You’ll own local data connections and work closely with operators, technicians, and process engineers. The ideal candidate has an engineering degree with ML/analytics exposure, a strong plant-floor instinct,

Qualifications

• Bachelor's degree in Engineering (Mechanical/Industrial/Electrical) with coursework in ML or analytics.
• Experience applying ML/data analytics in manufacturing or industrial settings.
• Strong plant-floor instincts and ability to work with operators and engineers.

Responsibilities

• Identify losses on the line (scrap, downtime, quality escapes) and apply AI/analytics to address them.
• Build and deploy models on plant data for coating, formation quality, and yield root cause analysis.
• Translate model outputs into actions: parameter changes, error-proofing and standard work with process controls and quality.
• Share findings and reusable assets with the central technologist to benefit multiple plants.
• Own the local data connections: MES, historians, PLC and OT data, and inline metrology.

Skills

ML

Data analytics

Python

Education

Bachelor's degree in Engineering

Tools

MES systems

PI Historian

Ignition

PLC data

Job description

Ford Energy is seeking a data and analytics-driven engineer to drive continuous improvement on yield, scrap, quality, and throughput. You will partner with central technologists to build and deploy models on plant data, then turn outputs into actionable parameter changes and standard work.

You’ll own local data connections and work closely with operators, technicians, and process engineers. The ideal candidate has an engineering degree with ML/analytics exposure, a strong plant-floor instinct,