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Dell

Senior Software Engineer

Dell
ElectronicsSingapore, SingaporeOnsitePosted 3 weeks ago
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About the role

AI summarised

Senior software engineer role focused on building AI/ML software and backend services for Dell's client PC AI ecosystem. Responsibilities include developing model evaluation platforms, deploying AI solutions on client silicon, and optimizing ML models for edge devices using containerized environments and hardware vendor toolchains.

ElectronicsOnsite

Key Responsibilities

  • Design and implement backend services and APIs to support the Model Evaluation Platform (MEP) for AI model benchmarking
  • Develop and deploy AI/ML software solutions tailored for client silicon, integrating telemetry and performance metrics
  • Build and manage containerized applications using Docker and orchestrate deployments with Kubernetes (K8s)
  • Automate system-level tasks using shell scripting to streamline development, deployment, and telemetry workflows
  • Collaborate with data scientists and ML engineers to optimize model lifecycle, telemetry integration, and AI/ML models execution
  • Conduct experiments to train and optimize Machine Learning / Deep Learning models for delivery onto client devices

Requirements

  • Bachelor's degree + 5 years, Master's + 3 years, or PhD in Computer Science, Engineering, AI/ML, or related fields
  • Strong proficiency in Python, RUST and C++ for backend, apps and performance-critical components
  • Experience with shell scripting for automation and system orchestration
  • Proven expertise in backend service development and API design
  • Hands-on experience with Kubernetes (K8s) and Docker for container orchestration and deployment
  • Solid understanding of Software Development Life Cycle (SDLC) and agile methodologies
  • Experience developing for Microsoft Windows OS, including SDKs and embedded device development in RTOS environments
  • Strong knowledge of embedded systems and their application in client ecosystems
  • Experience with AI software development tools, such as model quantization frameworks, inference optimization libraries, or agentic AI platforms
  • Familiarity with development in real-time embedded environments and major hardware vendor toolchains (e.g., Intel OpenVino, Qualcomm QNN, NVIDIA CUDA, AMD Ryzen AI Software)
  • Prior work on model evaluation frameworks or benchmarking systems for edge AI