Machine Learning / AI Engineering Co-op (Winter 2026)

About FirstPrinciples:
FirstPrinciples is a non-profit organization building an autonomous AI Physicist designed to advance humanity's understanding of the fundamental laws of nature. Our goal for the AI Physicist is to achieve a breakthrough that unifies quantum field theory & general relativity and to explain the deepest unresolved phenomena in our universe by 2035. To do this, we're pioneering a new approach to scientific discovery by creating an intelligent system that can explore theoretical frameworks, reason across disciplines, and generate novel insights. We're a non-profit that operates like a tech start-up by moving quickly and continuously iterating to accelerate scientific progress. By combining AI, symbolic reasoning, and autonomous research capabilities, we're developing a platform that goes beyond analyzing existing knowledge to actively contribute to physics research.

Job Description:
We're seeking Machine Learning / AI Engineering Co-ops for a full-time, 4-month term (January–April 2026). This remote role can be based anywhere in Canada. As a co-op, you will join a team focused on challenges at the intersection of scale, intelligence, and reasoning, contributing to the development of next-generation AI models and agentic frameworks for scientific discovery..

Key Responsibilities:

Depending on your strengths and interests, you might work on:

• Building and optimizing large-scale data and model training workflows for pre-training pipelines.
• Experimenting with reinforcement learning from human feedback, reasoning benchmarks, and alignment methods for fine-tuning and evaluation.
• Designing and scaling multi-agent systems that coordinate reasoning tasks across specialized models for model orchestration.
• Contributing to internal frameworks that enable persistent, memory-augmented AI agents.
• Exploring neural-symbolic architectures and applying LLMs to computational math problems.
• Developing distributed training, inference, and evaluation systems for scale infrastructure.
• Augmenting, designing, and inventing various tools within the ecosystem with interactive user interfaces for UI, graphics, and event-driven programming.

You will own a well-defined project and be treated as a full contributor, with your code potentially going into production and your experiments informing papers and deployed systems.

Qualifications:

• Educational Background: Currently pursuing a degree in Computer Science, Engineering, Math, Physics, or a related discipline.
• Experience:
• Hands-on work in Python, PyTorch, CUDA or Warp or JAX, React, typescript, webGL
• Comfort with distributed or large-scale training environments
• Personal or research projects in ML, LLMs, reinforcement learning, or infrastructure systems
• Skills: Strong programming skills in at least one compiled/systems language (Python, Go, or Rust).
• Collaboration & Communication: Ability to work cross-functionally. Strong communicator who can simplify complex topics for diverse audiences.
• Mindset: Entrepreneurial & mission-driven, comfortable in a fast-growing, startup-style environment, and motivated by the ambition of tackling one of the greatest scientific challenges in history.
• Demonstrated passion for physics and for making scientific knowledge accessible and impactful.
• Hands-on work in Python, PyTorch, CUDA or Warp or JAX, React, typescript, webGL
• Comfort with distributed or large-scale training environments
• Personal or research projects in ML, LLMs, reinforcement learning, or infrastructure systems

Bonus Skills:

• Contributions to open-source ML frameworks
• Experience with fine-tuning pipelines
• Track record of building tools around reasoning, math, or symbolic systems.

Application Process:

• Interested candidates are invited to submit their resume, a cover letter detailing their qualifications and vision for the role, and references. Please include "Machine Learning / AI Engineering Co-op (Winter 2026)" in the cover letter.

Join us at FirstPrinciples and be a part of a transformative journey where science drives progress and unlocks the potential of humanity.