Principal AI Engineer

Vertiv•Delaware, OH

3d•Onsite

About The Position

We are seeking a Principal AI Engineer (software computer engineering or electrical engineering background) with a strong product-development foundation to lead AI initiatives that accelerate time-to-market, improve engineering efficiency, and enable AI-driven product capabilities. This role spans five product lines within the IT Rack Infrastructure domain and supports AI efforts across sustaining engineering, New Product Development and Introduction (NPDI), and forward-looking blue-sky research. The ideal candidate combines deep technical credibility in real-world product development with a creative, research-oriented mindset to explore breakthrough AI methods and technologies that can redefine both engineering processes and products.

Requirements

Master’s degree or PhD in Electrical Engineering, Computer Engineering, or related technical field.
10+ years of experience computer engineering or electrical engineering or advanced research in related fields.
5+ years of experience in AI/ML development, applied machine learning, embedded systems and advanced analytics.
Strong proficiency in: Python, ML frameworks (TensorFlow, PyTorch, scikit‑learn) Data engineering and MLOps tools Model validation, testing, and deployment practices
Experience deploying AI/ML models in embedded systems, cloud platforms, or distributed systems.
Ability to provide technical leadership and drive cross-functional initiatives.
Familiarity with IT rack systems and infrastructure components is a plus.
Demonstrated ability to conceptualize and validate transformative ideas in mechanical design and materials applications.
Strong communication and presentation skills.
Ability to work both independently and collaboratively, engaging with cross-functional teams and external partners effectively.

Nice To Haves

Experience in energy technologies, IoT, or industrial/embedded products.
Knowledge of digital twins, simulation environments, or control systems.
Familiarity with edge AI inference frameworks and optimized runtime environments.
Track record of patents, high quality research/publications, or technical presentations.
Having research articles in ICML, ICLR or L4DC conferences is a plus

Responsibilities

Lead and explore AI-related research and emerging AI-technologies focused on IT Rack Infrastructure products (1PH UPS, rack-based power distribution units, KVM and Serial devices, mechanical racks).
Define the AI/ML architecture and technology roadmap for the IT Systems Business Unit.
Identify high‑value AI use cases across single‑phase UPS, rack PDU, KVM/Serial, racks, and integrated solutions.
Drive alignment of AI initiatives with product-line strategies and long-term business goals.
Lead feasibility studies, prototypes, and proof-of-concept developments.
Ensure AI/ML model’s robustness, performance, explainability, and lifecycle management.
Lead AI initiatives for improving our NPDI process time-to-market and engineering efficiency.
Work with engineering leaders across product lines to define technological needs and feasibility.
Collaborate with embedded software and firmware teams to deploy models on constrained edge devices and real-time systems.
Define requirements for data acquisition, signal conditioning, and model inference hardware/software.
Establish practices for data collection, preprocessing, labeling, and governance.
Implement Machine Learning Operations (MLOps) frameworks for continuous integration, testing, versioning, and monitoring of AI models.
Develop prototype methods, models, and simulations to validate new ideas and support technology feasibility studies.
Collaborate closely with cross-functional teams, including product development, engineering, and infrastructure teams, to ensure alignment of research objectives with overall company vision and market trends.
Publish technical papers, file patents, and present findings to internal stakeholders and external audiences, contributing to the organization’s knowledge base and thought leadership.
Identify and collaborate with external research institutions, industry partners, and academic organizations to leverage additional expertise and insights.
Engage with standards bodies, and technology partners.
Mentor and guide junior engineers, fostering a culture of curiosity, creativity, and technical excellence within the team.