High-Performance Machine Learning Software Specialist

6 days ago

Singapore beBeeHardware Full time $80,000 - $120,000

Machine Learning Software Engineer

Job Overview:

We are seeking a talented and driven machine learning software engineer to design, develop, and optimize software systems for AI computing platforms.

  • Design, develop, and optimize the software architecture and source code for AI computing platforms that support machine 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:
  • Bachelor's degree in Computer Science, Electrical Engineering, or a related field.
  • 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).
  • Strong problem-solving skills and the ability to optimize software performance for AI workloads.
Preferred Qualifications:
  • Experience with deep learning frameworks and tools for performance profiling and optimization.
  • Knowledge of low-level hardware optimization techniques (e.g., memory management, CPU/NPU/GPU instruction tuning).
  • Familiarity with system-level software for AI computing platforms, such as TensorRT or ONNX Runtime.
  • Background in designing and implementing high-performance distributed systems and storage solutions.
  • Strong understanding of networking, I/O, and data management techniques for AI workloads.

We look forward to hearing from you

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