POSITION SUMMARY
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.
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.
REQUIRED QUALIFICATIONS
- 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.
PREFERRED QUALIFICATIONS
- 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
KEY COMPETENCIES
- Strong systems thinking and problem-solving ability
- Technical leadership and communication
- Strategic planning and innovation mindset
- Ability to navigate complex, cross-functional organizations
- Focus on scalability, reliability, and productization
PHYSICAL & ENVIRONMENTAL DEMANDS
- Office and lab environment. Must be comfortable working in a lab performing or guiding experiments.
TRAVEL REQUIRED
- 10%
#LI-RB1