AI Computing Platform Software Engineer

1 week ago

Singapore beBeeSoftware Full time $100,000 - $150,000
Job Overview

We are seeking a talented and driven software engineer to join our cutting-edge engineering team. In this role, you will be responsible for designing and developing software systems that power AI computing platforms. Your work will focus on optimizing performance, scalability, and efficiency for AI workloads, ensuring our platform meets the growing demands of machine learning and deep learning models.

Key Responsibilities:

  • Design, develop, and optimize the software architecture and source code for AI computing platforms that support machine learning and deep learning workloads.
  • Implement and enhance algorithms for distributed computing, parallel processing, and NPU/GPU acceleration.
  • Work on software components that interface with hardware accelerators such as NPUs, GPUs, and specialized AI chips.
  • Collaborate with AI researchers and developers to improve platform performance for complex AI applications.
  • Design and implement tools and frameworks for efficient deployment, monitoring, and scaling of AI workloads.
  • Integrate new AI models and algorithms into the computing platform while ensuring scalability, fault tolerance, and efficiency.
  • Collaborate with cross-functional teams to troubleshoot and resolve platform-related performance issues.
  • Conduct performance profiling, optimization, and benchmarking to ensure the platform delivers high throughput and low latency for AI workloads.
Required Skills and Qualifications

The ideal candidate should possess:

  • A Master's degree in Computer Science, Electrical Engineering, or a related field (PhD preferred).
  • Extensive experience in developing high-performance software for computing platforms, ideally with a focus on AI/ML workloads.
  • Strong programming skills in languages such as C/C++, Python, or Go, with a focus on low-level programming for high-performance systems.
  • In-depth knowledge of parallel programming techniques and distributed systems.
  • Experience with GPU programming (CUDA, OpenCL) or specialized hardware accelerators (e.g., NPUs, FPGAs).
  • Familiarity with machine learning frameworks such as PyTorch, TensorFlow, or MXNet.
  • Understanding of AI model deployment, orchestration, and optimization on large-scale platforms.
  • Experience with containerization (Docker, Kubernetes), AI computing platform (HuggingFace, Kaggle), and cloud infrastructure (AWS, GCP, Azure).
Benefits and Opportunities

Successful candidates can expect:

  • A dynamic and collaborative work environment.
  • Opportunities for professional growth and development.
  • A competitive compensation package.
How to Apply

Interested candidates should submit their resumes and cover letters via the provided link.

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