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.
The Role:
As a Senior Software Engineer- Low Voltage Prognostics 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.
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