Research Software Development Engineer

4 weeks ago

Toronto, Ontario, Canada Skyfall AI Full time

About the company

Skyfall is disrupting the entire AI ecosystem by building the first world model for the enterprise. The goal of the 'Enterprise world Model' is to overcome the severe limitations of LLMs (Safety, Hallucinations, Expensive training) in order to provide the enterprises significant value by having a comprehensive understanding of the complex interplay between data, people and processes with organizations.

The Skyfall founding team consists of Maluuba founders who were previously pioneers in the Deep learning revolution. Maluuba worked with AI pioneers such as Yoshua Bengio and Richard Sutton before it was acquired by Microsoft for $160M and became Microsoft's AI research center in Canada.

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 AI training infrastructure, pushing the boundaries of LLMs and RL, and contributing to the broader research community through publications and open-source projects.

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.
  • Optimize AI Model Performance – Collaborate with researchers to improve training efficiency, fine-tuning strategies, and inference optimization for real-world enterprise applications.
  • 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, with experience in software engineering best practices.
  • Experience with cloud-based GPU training environments (e.g., AWS, Lambda Labs, GCP).
  • Hands-on experience with open-source AI frameworks (e.g., PyTorch, TensorFlow, JAX).
  • Experience working with large-scale distributed systems and training pipelines.
Nice to Have Qualifications:
  • Master's degree in Computer Science, Machine Learning, or a related technical field.
  • Published research in top AI/ML conferences (e.g., NeurIPS, ICML, ICLR, ACL).
  • 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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