Principal Software Engineer

This role is responsible for the design of advanced technology solutions to support the business strategy and objectives, with a particular focus on integrating AI models into AI-powered PCs. The role involves leading the development of innovative technology solutions that enable strategic initiatives to scale the business effectively and efficiently. A key aspect of this position is driving the operational excellence of AI model deployment, ensuring high-performance standards, and integrating cutting-edge AI technologies into systems. The role involves managing the departmental budget, setting team goals/KPIs, and driving performance management of direct reports, all while collaborating closely with cross-functional teams to ensure the successful implementation of complex AI-driven systems.

Responsibilities

• Plays a leading role in the development and integration of AI models (e.g., LLMs, SD, RL) into AI-powered PCs, ensuring alignment with business, technical, and security requirements.

• Leads the establishment of engineering standards, architectures, and the automation of software deployment processes within the context of AI models in production environments.

• Designs and develops end-to-end solutions for managing, protecting, and optimizing AI model performance within complex hardware and software systems.

• Drives strategic technology roadmaps and AI model integration plans for AI PC platforms, ensuring scalability, efficiency, and alignment with business objectives.

• Provides mentorship and technical guidance to teams responsible for data processing, model training, and fine-tuning (using tools like TensorFlow, PyTorch, etc.).

• Ensures that AI model deployment is optimized for performance on edge devices and AI PCs, leveraging hardware accelerators such as GPUs and NPUs.

• Works closely with cross-functional teams, including product management and design, to drive product and software features from concept to deployment.

• Develops innovative solutions to complex, unique problems affecting AI model deployment, tuning, and optimization in production environments.

• Provides leadership on functional strategy and policy development for AI integration across teams.

• Acts as a senior-level decision-maker and thought leader in AI model integration and performance optimization within the organization.

Education & Experience Recommended

• Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, or a related discipline, or equivalent work experience.

• Typically has 12+ years of industry experience, with a proven track record in AI model integration, optimization, and large-scale software development, particularly within AI-driven hardware systems.

Preferred Certifications

• Programming Language/s Certification (Java, C++, Python, JavaScript, or similar).

Knowledge & Skills

• Experience running and integrating AI models (e.g., LLMs, SD, RL, etc.) in production environments, particularly for AI PC applications. Bonus points for expertise in optimizing AI model deployment and performance.

• Expertise in processing data, training, and fine-tuning models using frameworks such as TensorFlow, PyTorch, PEFT, and similar tools.

• Experience with on-edge inference techniques (e.g., ONNX, OpenVINO, QNN, TensorFlow Lite, Libtorch) and deploying models in constrained environments.

• Proficiency in at least two of the following languages: Python, C++, C#, C, Java, Scala.

• Extensive experience in performance evaluation, optimization of software, and AI model inference, particularly in hardware-constrained environments.

• Proven expertise in memory reduction, optimization techniques, and leveraging hardware acceleration for AI models (e.g., GPU, NPU).

• Strong experience working with multiple CPU platforms (e.g., AMD, Intel, ARM (AARCH64)) and optimizing for each platform’s specific capabilities.

• Deep understanding of AI model integration within AI-powered PCs, ensuring smooth performance across both hardware and software layers.

Cross-Org Skills

• Strong Leadership and Communication skills

• High Results Orientation

• Advanced Learning Agility and Digital Fluency

• Customer-Centric Thinking and Problem-Solving