Research Software Engineer Job at Skyfall AI, Canada

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  • Skyfall AI
  • Canada

Job Description

Job Description

Job Overview:

Skyfall AI is on a mission to build the future of autonomous enterprises, and we're looking for a Research Software Development Engineer (RSDE) to join our cutting-edge AI research team. This role is ideal for engineers who thrive at the intersection of AI research and scalable software engineering, working on next-generation language models, reinforcement learning, and multi-agent systems. You’ll play a key role in developing new tools and techniques for training the next generation AI systems.

Key Responsibilities:
  • Develop Scalable AI Infrastructure – Design and build high-performance training pipelines for language models, reinforcement learning agents, and multi-agent systems.
  • Implement Cutting-Edge AI Techniques – Work with state-of-the-art architectures, including transformer models, reinforcement learning frameworks, and generative AI techniques.
  • Develop and extend training environments based on existing business simulator games
  • Contribute to Research & Open Source – Publish high-impact research, engage with the broader AI community, and contribute to leading open-source AI projects.
  • Work with Large-Scale Systems – Leverage cloud-based GPU environments and distributed computing frameworks to train and deploy large-scale AI models.

Minimum Qualifications:
  • Bachelor's degree in Computer Science, Machine Learning, or a related technical field.
  • Strong programming skills in Python ,C/C++ and Node, with experience in software engineering best practices.

Nice to Have Qualifications:
  • Master’s degree in Computer Science, or a related technical field.
  • Experience with cloud-based GPU training environments (e.g., AWS, Lambda Labs, GCP).
  • Hands on experience in game environments such as pygame
  • Hands-on experience in RL learning environments such as Open AI Gym, TextWorld etc.
  • Hands-on experience with open-source AI frameworks (e.g., PyTorch, TensorFlow, JAX).
  • Experience working with large-scale distributed systems and training pipelines.
  • Hands-on experience in LLMs, reinforcement learning, or multi-agent systems.
  • Experience optimizing training pipelines for large-scale AI models.
  • Contributions to open-source AI projects or AI research communities.

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