Maincode
AI Research Resident
1mo ago
WorldwideJuniorRemotegpu computemodel researchsystem infrastructure
AI Research Residency program for late-stage PhD students and early-career researchers focused on applied AI research to advance real-world AI systems.
Responsibilities
- Lead research that advances Maincode's work on capable, useful, and trustworthy AI systems.
- Design and execute experiments, develop new research directions, and collaborate closely with our researchers and engineers.
- Produce research outputs suitable for top-tier conferences, journals, technical reports, open-source releases, or deployment in Matilda and future Maincode systems.
Requirements
- Late-stage PhD student, recent PhD graduate, or exceptional early-career researcher.
- Strong research taste and the ability to identify important problems before they are obvious.
- Experience publishing, preprinting, or producing high-quality research in AI, machine learning, or adjacent technical fields.
- Ability to define and execute independent research under uncertainty.
- Interest in building AI systems that can reason, act, and operate reliably in complex real-world environments.
Other
- Maincode is an Australian AI research company building Matilda, an assistant that understands complex work, reasons over context, and takes meaningful action safely.
- The AI Research Residency is a paid 3 to 6 month program for late-stage PhD students and exceptional early-career researchers who want to pursue high-impact AI research grounded in real systems.
- Residents work closely with Maincode's research and engineering teams, with dedicated access to large-scale GPU compute and our in-house research infrastructure. You will explore open problems, run experiments at scale, and produce work that can contribute to top-tier publications, open research, infrastructure, or the systems behind Matilda.
- This role is research-first, but applied. Strong projects may take the form of model research, evaluations, infrastructure, technical engineering work, or product-facing research that improves Matilda and future Maincode systems.
- We are interested in research that makes AI systems more capable, reliable, efficient, and useful in the real world.
- The residency program is primarily focused on the following areas:
- Tool use, planning, memory, computer control, multi-agent systems, and safe execution in real-world environments.
- Long-context reasoning, workflow understanding, state tracking, memory systems, and methods for maintaining coherence across complex tasks.
- Capability evaluations, alignment, oversight, interpretability, robustness, red-teaming, and benchmarks for real-world task completion.
- Language model training, reinforcement learning, reasoning methods, optimisation, architectures, and new approaches to improving model behaviour.
- Data curation, filtering, synthetic data, mixture design, quality verification, pruning, and principled approaches to training signal.
- Vision-language models, grounding, perception, multimodal reasoning, and systems that combine language, visual context, and action.
- Training and inference efficiency, kernels, parallelism, sharding, decoding, quantisation, scheduling, and systems for running large models reliably.
- Dedicated access to Maincode's GPU compute and research infrastructure.
- Close collaboration with a small, high-calibre team across AI research, systems engineering, product engineering, and design.
- Support for top-tier conference and journal submissions, with the opportunity for strong research to contribute to Matilda and future Maincode systems.
- A research environment focused on deep work, technical seriousness, and real-world impact.