Senior Neural Network Engineer - Remote

4 days ago

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A5 Labs

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A5 Labs is a pioneering company that focuses on data, machine learning, and blockchain technologies to enhance the integrity and fairness of competitive online games. Comprising a team of tech entrepreneurs, AI scientists, and passionate gamers, A5 Labs aims to address the challenges faced by the online gaming industry, including issues related to game integrity and player matchmaking. The company leverages advanced analytics, artificial intelligence, and blockchain platforms to create transparent gaming experiences and ensure fair play for all users.

Game Theory Research • Machine Learning • Business Intelligence • Online Gaming • Game Design

51 - 200 employees

🎮 Gaming

🤖 Artificial Intelligence

📋 Description

• Design and develop advanced neural network architectures, with a focus on transformers and reinforcement learning models for real-world applications. • Lead efforts in large-scale training of neural networks, employing tools like TensorFlow and PyTorch to deliver high-performing, optimised models. • Proven expertise in large-scale neural network training, addressing industry challenges like data scarcity and noise. • Implement and manage tools for gradient-based techniques, feature attribution, and model interpretability. • Monitor model performance with analytical rigour, ensuring robust, reliable outcomes. • Apply advanced optimization skills including pruning, quantization, regularisation techniques, ensemble and knowledge distillation, and hyperparameter tuning through Bayesian optimization or other methodologies to enhance model performance and scalability.

🎯 Requirements

• 3+ years of professional experience working with neural networks, particularly in AI-driven industries or leading research organisations. • Proficient in TensorFlow, PyTorch, and other deep learning frameworks. • Extensive experience in neural network analysis, including advanced interpretability and performance analysis techniques. • Solid understanding of reinforcement learning, transformers, and LLMs. • Hands-on experience with optimization strategies, such as advanced optimizers, pruning, quantization, and hyperparameter tuning. • Demonstrated record of research publications achieving state-of-the-art neural network performance. • Proven experience in large-scale neural network training and addressing industry-specific challenges like data scarcity, noise, and high-variance data sources.