Machine Learning Engineer

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🕒 March 31

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Quincus

201 - 500 employees

Founded 2014

🛍️ eCommerce

🤖 Artificial Intelligence

💰 Series B on 2021-11

Logistics & Supply Chain • eCommerce • Artificial Intelligence

Quincus is a digital supply chain orchestration company that leverages artificial intelligence to enhance logistics and supply chain operations. By providing AI-powered solutions, Quincus offers real-time logistics data and a unified platform to boost efficiency, ensure cost-effective shipments, and streamline workflows. The company focuses on improving shipment visibility, address accuracy, and delivery optimization, while offering scalable API integration solutions to simplify communication across logistics networks. Quincus serves industries including logistics and supply chain, retail and e-commerce, and life sciences, aiming to empower a productive workforce and facilitate seamless global operations.

📋 Description

• Design and implement scalable systems for serving deep learning and reinforcement learning models. • Optimize inference performance of deep learning and reinforcement learning models using techniques such as quantization, pruning, and distillation. • Utilize GPU computing to accelerate model training and inference. • Develop and deploy production workflows for training and serving machine learning models. • Collaborate with data scientists and software engineers to design and implement machine learning systems. • Monitor and improve the performance of machine learning models in production. • Stay up-to-date with the latest research and techniques in deep learning and reinforcement learning.

🎯 Requirements

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field. • 3+ years of experience in software engineering or machine learning engineering. • Strong programming skills in Python (C++ or Java a plus) • Experience with deep learning frameworks such as TensorFlow or PyTorch. • Experience with GPU programming using CUDA, OpenCL, or similar libraries. • Experience with distributed systems and cloud computing platforms such as Kubernetes, Docker, GCP, and AWS.

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