About KorrAI

KorrAI is a YC-backed company helping asset owners and insurers monitor infrastructure remotely. We use satellite imagery and AI to identify risks affecting mines, data centers, railways, and other critical assets. Our mission is to make infrastructure risk visible, early, and actionable.About the Role

We are at the forefront of building next-generation AI systems, synergizing advanced ML models with robust tools and APIs to execute complex, agentic tasks. Our mission is to engineer systems that are robust, scalable, and intelligent, deeply grounded in fundamental scientific principles and a thorough understanding of modern AI’s mechanics.

The Role

As a Senior AI Systems Engineer, you will design, implement, and scale sophisticated AI agents powered by state-of-the-art LLMs. This role requires hands-on engineering connecting models, APIs, and external tools while also driving architectural decisions and exploring the why behind these systems. You will work at the intersection of applied engineering and advanced theory, engaging with concepts like neural scaling laws, the manifold hypothesis, dimensionality reduction, Langevin dynamics, diffusion models, and representation learning.

What You’ll Do

• Design and implement robust agentic pipelines, integrating LLMs with diverse tools and APIs.
• Optimize performance, parallelism, and scalability across GPUs and distributed systems.
• Translate abstract research directions into reliable production systems.
• Cultivate a deep intuition for model internals, bridging advanced theoretical insights with practical engineering solutions.
• Mentor junior engineers, sharing best practices in system design and scientific reasoning.

You’ll Thrive Here If You

• Are highly proficient in Python and experienced with PyTorch or JAX.
• Bring expertise in parallel/distributed programming and GPU acceleration.
• Have strong foundations in computer science fundamentals (algorithms, operating systems, computer architecture).
• Possess a solid conceptual and practical understanding of mathematical and physical principles relevant to AI, including linear algebra, probability, calculus, and statistical mechanics.
• Are curious, self-driven, and eager to push the boundaries of how complex AI systems operate under the hood.

Nice to Have

• Experience with multi-agent systems or contributions to open-source agent frameworks.
• Hands-on exposure to generative models, diffusion, or representation learning.
• Contributions to AI research, theoretical advancements, or impactful open-source projects.

Compensation

• Full-time salary: CAD 140,000 – 160,000 (depending on experience and impact).
• Competitive benefits and performance-based growth opportunities.