Senior Prognostics Engineer– Low Voltage

General Motors; Milford Charter Township (MI); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Hybrid work model

Relocation benefits

Job summary

General Motors in Michigan is seeking a Senior Prognostics Engineer- Low Voltage to design, validate, and deploy production-ready prognostic algorithms that predict and prevent low voltage failures across vehicle platforms.

You will model subsystem behavior, analyze field data, and collaborate with diagnostics, software, calibration, and service teams to translate telemetry into actionable insights while supporting production rollout and safety compliance.

Qualifications

• Bachelor's degree in Engineering or Computer Science.
• 5+ years in automotive prognostics, diagnostics, embedded controls, or data analytics.
• Strong experience in Python, major ML frameworks, and SQL.
• Experience with Power BI, Databricks, and Azure analytics platforms.
• Analytical and problem-solving with data-driven decision-making.
• Ability to translate ambiguous problems into clear requirements and solutions.
• Strong communication and collaboration across cross-functional teams.

Responsibilities

• Design, develop, and deploy prognostic algorithms for low voltage components and parasitic drain detection (lithium ion batteries).
• Model low voltage system behavior and failure modes; monitor degradation trends over vehicle life.
• Pilot and validate prognostic features in development and test fleets, then support production rollout.
• Partner with diagnostics, service engineering, vehicle health management, analytics, and aftersales to ensure prognostics outputs are actionable and integrated into tools and notifications.
• Analyze field data to evaluate alert effectiveness and tune thresholds and calibrations.
• Collaborate with architecture and safety teams to ensure prognostic strategies meet system safety goals, ASIL targets, and regulatory requirements.
• Develop roadmaps and strategy for low voltage prognostics across architectures, programs, and model years.
• Apply statistical analysis, anomaly detection, clustering, and signal processing to uncover new patterns in vehicle telemetry data.

Skills

Python

Machine Learning

SQL

Power BI

Databricks

Azure Apps

Data Visualization

Analytical Thinking

Cross-functional Collaboration

Education

Bachelor's degree in Engineering or Computer Science

Master's degree (preferred)

Tools

PySpark

MATLAB

Job description

The Team

The Low Voltage Infrastructure (LVI) team develops the systems and controls that generate, store, distribute, and manage low voltage power across our entire portfolio of vehicles. Our work highly impacts the customer experience and vehicle reliability.

Job Description

The Low Voltage Infrastructure (LVI) team develops the systems and controls that generate, store, distribute, and manage low voltage power across our entire portfolio of vehicles. Our work highly impacts the customer experience and vehicle reliability.

As a Senior Prognostics Engineer- Low Voltage within LVI, you’ll design, validate, and deploy production-ready prognostic algorithms that predict and prevent low voltage failures. Your work will detect parasitic drains, assess electrical system health, and enable timely service and customer interventions—reducing walk‑home events and unnecessary warranty expense.

You’ll collaborate closely with systems, diagnostics, software, calibration, quality, and service teams to turn vehicle data into scalable, field‑proven prognostic algorithms. This is an assignment where creativity, analytical thinking, deep customer insight, and exceptional collaboration are crucial and celebrated!

What You'll Do (Responsibilities)

• Design, develop, and deploy prognostic algorithms for low voltage components and parasitic drain detection (lithium ion batteries).
• Model low voltage system behavior and failure modes; monitor degradation trends over vehicle life.
• Pilot and validate prognostic features in development and test fleets, then support production rollout.
• Partner with diagnostics, service engineering, vehicle health management, analytics, and aftersales to ensure prognostics outputs are actionable and integrated into tools and notifications.
• Analyze field data to evaluate alert effectiveness and tune thresholds and calibrations.
• Collaborate with architecture and safety teams to ensure prognostic strategies meet system safety goals, ASIL targets, and regulatory requirements.
• Develop roadmaps and strategy for low voltage prognostics across architectures, programs, and model years.
• Apply statistical analysis, anomaly detection, clustering, and signal processing to uncover new patterns in vehicle telemetry data.

Your Skills & Abilities (Required Qualifications)

• Bachelor's degree in Engineering or Computer Science.
• Minimum 5+ years of engineering experience related to automotive prognostics, diagnostics, embedded controls, or data analytics.
• Strong experience in Python, major machine learning frameworks, and SQL.
• Experience with data visualization and analytics platforms (i.e. PowerBI, Databricks Apps, Azure Apps).
• Exceptional analytical and problem-solving skills, with a track record of data-driven decision making.
• Demonstrated ability to turn ambiguous problems into clear requirements, value proposition, models, and technical solutions.
• Strong communication and collaboration skills, with experience working across cross-functional teams.

What Will Give You A Competitive Edge (Preferred Qualifications)

• Master's degree (or higher) in Engineering or Computer Science.
• Experience developing prognostics for low voltage systems, energy storage, power conversion, or load management.
• Experience with degradation modeling and long‑term health monitoring.
• Understanding of vehicle manufacturing, service, and warranty processes—including how prognostic content flows into service tools and customer‑facing messages.
• Familiarity with functional safety (ISO 26262, ASIL) and their impact on system and software design.
• Experience with advanced analytics techniques, LLMs, or AI‑enabled tooling applied to vehicle health, prognostics, diagnostics, or service insights.
• Experience with PySpark.
• Experience with Matlab.

This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}. This job may be eligible for relocation benefits.

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Benefits Overview

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Non-Discrimination and Equal Employment Opportunities (U.S.)

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