Plus10 is a technical recruitment agency with a focus on Engineering and Product professionals that build web applications using a modern stack. Plus10 recruiters are knowledge stewards that open doors for individuals looking to progress their career. We are working hand-in-hand with the following client to help find a Member Of Technical Staff, Research The client is a non-profit organization building an autonomous AI Physicist designed to advance humanity's understanding of the fundamental laws of nature. The goal is 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.

They'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. The organization 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, to develop a platform that goes beyond analyzing existing knowledge to actively contribute to physics research.

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We are looking for a Member of Technical Staff, Research to investigate, design, test and develop state of the art (SOTA) methods and applications, which can be integrated into the broader AI engine FirstPrinciples is developing. You will collaborate with cross-functional teams and your work will flow straight into production, helping advance the way scientific research is performed. Your work will impact the wider academic community through the development of unique solutions to usher in a new era of scientific discovery.

The ideal candidate has a proven track record in AI research,



who can combine strategic thinking with technical depth to bring complex ideas to life.

Key Responsibilities

Fundamental Model Research:

- Research, design, and test novel, research‑specific model architectures that integrate academic literature, natural language processing (NLP), symbolic reasoning, and other methods to orchestrate the scientific process.
- Prototype and build custom tokenizers for LaTeX symbols and physical units to be treated as tokens.
- Explore alternatives to transformers through in-depth research and provide practical recommendations for model development.
- Develop reinforcement-learning loops to enable models to run independent and internal thought experiments.

Multimodal Data & Benchmarking:

- Design and automate data ingestion pipelines in collaboration with our Data Scientists & Engineers that aggregates science literature, metadata, experimental data, equations and other data sources in a robust and scalable manner.
- Establish custom benchmarks to assess the models’ understanding of physical concepts, mathematical reasoning abilities, and ability to minimize hallucinations for the benefit of scientific reliability.
- Refine and release datasets and baselines once internal tests are secure.

Training, Testing & Safety:

- Run and track model training jobs while leading the technical team through set-up, monitoring progress, and constraining costs within budget.




- Develop approaches to stage “practice runs” in a sandbox environment to develop the model’s abilities to explore ideas independently while logging results for later review.
- Develop a framework to evaluate the models’ learning using visual and statistical tools to spot patterns and blind spots.
- Add guard-rails and tests that flag poor quality model output.
- Maintain internal tools to track lists of known issues, noting failures, clear fixes, and improvements to be integrated into future development

Collaboration & Technical Guidance:

- Work with the engineering team to ensure product feasibility and robust architecture.
- Translate technical trade-offs to non-technical stakeholders in clear terms.
- Present findings in clear updates to the technical team in order to keep the broader team appraised of progress against research milestones.

Qualifications:

- Educational Background: PhD in physics, computer science, data science, information systems, or related field.
- Experience: Proven track record of conducting in-depth research on scientific AI models, symbolic models, machine learning or deep learning for scientific discovery.
- Technical Skills: Familiarity with SOTA models, best practices in model development processes, in-depth AI/ML concepts, and data infrastructure.
- Collaboration & Communication:
- Comfort working closely with engineers and other technical team members.
- Strong written and verbal communication skills.
- Comfortable working in a startup-style, cross-functional, remote team.

- Bonus Skills:

- Has experience with or strong interest in physics and/or fundamental science topics.
- Experience conducting research on AI models in an early-stage or mission-focused environment.

Discuss with your Plus10 Recruiter or complete the form below to apply for this role.

📌 Member of Technical Staff, Research (Canada)
🏢 Plus10 Recruitment
📍 Canada