AI Cold Chain Optimisation Specialist
2 weeks ago
We are seeking a skilled professional to enhance the performance and efficiency of our AI-powered solutions within our cold chain logistics network.
This role will play a critical part in ensuring the reliability, scalability, and performance of AI models powering our automated warehouse processes.
Key Responsibilities:- Implement model optimization techniques such as quantization and knowledge distillation to reduce model size and improve inference speed for deployment on edge devices and cloud infrastructure.
- Develop and maintain CI/CD pipelines for automated model deployment and updates, ensuring seamless integration with existing systems.
- Benchmark and profile model performance (latency, throughput, memory usage) to identify bottlenecks and areas for improvement.
- Deploy and manage machine learning models using model serving frameworks like TensorFlow Serving, TorchServe, ONNX Runtime, or Triton Inference Server.
- Containerize AI models and applications using Docker and Podman for consistent and reproducible deployments.
- Collaborate with data scientists and software engineers to troubleshoot model performance issues and implement solutions.
- Monitor model performance in production and proactively address any degradation in accuracy or efficiency.
- Develop and maintain APIs/SDKs (REST, gRPC, FastAPI) for accessing and integrating AI models into various applications.
- Work with edge devices (NVIDIA Jetson, Coral TPU, ARM-based boards) and edge frameworks (TensorRT, OpenVINO, TFLite, TVM) to optimize models for low-power, real-time inference.
- Bachelor's or master's degree in computer science, Artificial Intelligence, Machine Learning or a related field
- 1-3 years of experience in a role focused on machine learning model optimization and deployment
- Proficiency in Python and C++ programming languages
- Hands-on experience with model serving frameworks (TensorFlow Serving, TorchServe, ONNX Runtime, Triton Inference Server)
- Experience with containerization technologies (Docker, Podman) and orchestration tools (Kubernetes, K3s, Edge orchestrators)
- Knowledge of model optimization techniques such as quantization and knowledge distillation
- Familiarity with benchmarking and profiling tools for evaluating model performance
- Strong analytical and problem-solving skills with a data-driven approach
- Experience with CI/CD pipelines for ML deployment is highly desirable
- Knowledge of edge devices (NVIDIA Jetson, Coral TPU, ARM-based boards) and edge AI frameworks (TensorRT, OpenVINO, TFLite, TVM) is a significant plus
- Opportunity to work on cutting-edge AI applications in a rapidly growing and innovative cold chain logistics company
- Exposure to a wide range of AI technologies and challenges within a highly automated warehouse environment
- Career growth potential within a dynamic and international organization
- Collaborative and supportive team environment with opportunities for learning and development
- Contribute to the development of next-generation logistics solutions that are shaping the future of the food supply chain
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