Research Scientist

Required technical and professional expertise

Key ResponsibilitiesLead Cutting‑Edge AI Research

• Define and lead high‑impact research agendas in areas such as:
  • Generative computing inspired agentic development for small models
  • Reinforcement learning and decision‑making under uncertainty
  • Formal algebra and applications to AI Software Development
• Drive projects from problem formulation through theoretical analysis, experimentation, and system integration.

Develop Novel Algorithms and Techniques

• Small‑Model‑Friendly Agent Harnesses: Build evaluation and execution harnesses tailored for small, efficient models, enabling reliable agentic reasoning, tool use, and planning under tight latency and compute constraints.
• Develop new generative computing (see mellea.ai) architectures for next wave of AI software development. 
• Train customised models including data quality analysis, synthetic data generation, training and evaluation for small model agentic harnesses

Theory, Analysis, and Experimental Rigor

• Develop rigorous mathematical formulations and proofs to analyze algorithmic properties (e.g., convergence, generalization, robustness).
• Design statistically sound experiments, benchmarks, and ablations to validate research hypotheses.
• Measure impact on both offline metrics and end‑to‑end user experience.

Bridge Research and Real‑World Systems

• Embed research prototypes into production‑grade or large‑scale experimental systems.
• Collaborate with engineering teams to ensure research outcomes translate into robust, efficient, and usable AI solutions.

Publish and Communicate Research

• Publish and present original research in venues such as NeurIPS, ICML, ICLR, ACL etc
  • Communicate insights clearly to technical and business stakeholders.