Machine Learning Engineer
1 month ago
Quincus is a leading B2B supply chain operating SaaS platform headquartered in Singapore. We leverage cutting-edge technology to digitize and optimize logistics processes, providing customers with real-time transparency into their supply chain.
Job OverviewWe are seeking a highly skilled Machine Learning Engineer to join our team and contribute to the development and deployment of deep learning and reinforcement learning algorithms at scale. As a key member of our team, you will design and implement scalable systems for serving models, optimize inference performance, and manage production workflows.
Key Responsibilities- Design and Implement Scalable Systems: Develop and deploy deep learning and reinforcement learning models using scalable systems, ensuring high-performance and efficient inference.
- Optimize Inference Performance: Utilize techniques such as quantization, pruning, and distillation to optimize the performance of deep learning and reinforcement learning models.
- GPU Computing Expertise: Leverage GPU computing to accelerate model training and inference, ensuring optimal performance and efficiency.
- Production Workflow Development: Design and implement production workflows for training and serving machine learning models, ensuring seamless integration with our existing infrastructure.
- Collaboration and Communication: Work closely with data scientists and software engineers to design and implement machine learning systems, ensuring effective communication and collaboration throughout the development process.
- Performance Monitoring and Improvement: Continuously monitor and improve the performance of machine learning models in production, ensuring optimal results and efficiency.
- Education: Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
- Experience: 3+ years of experience in software engineering or machine learning engineering.
- Programming Skills: Strong programming skills in Python (C++ or Java a plus).
- Deep Learning Frameworks: Experience with deep learning frameworks such as TensorFlow or PyTorch.
- GPU Programming: Experience with GPU programming using CUDA, OpenCL, or similar libraries.
- Distributed Systems and Cloud Computing: Experience with distributed systems and cloud computing platforms such as Kubernetes, Docker, GCP, and AWS.
- Ph.D. in Computer Science or Electrical Engineering: Ph.D. in Computer Science, Electrical Engineering, or a related field.
- Advanced Experience: 5+ years of experience in software engineering or machine learning engineering.
- Reinforcement Learning Expertise: Experience with reinforcement learning algorithms and frameworks.
- Production Deployment: Experience with production deployment of machine learning models and implementation of APIs for big data.
- Computer Architecture and Performance Optimization: Strong understanding of computer architecture and performance optimization.
- Communication and Collaboration: Strong communication and collaboration skills.
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