Applied Scientist - Cubiq Recruitment

Our client is building context-aware agentic systems that augment data science, software, and product teams inside large enterprises. The systems reason over complex organisational data, take multi-step actions, and integrate deeply with existing business workflows. We are now expanding the Applied Science team and are looking for exceptional early-career researchers who want to work on cutting-edge ML in a fast-moving product environment.

This role is ideal for candidates finishing (or recently completing) a PhD at a top university, with a research track record at leading ML/AI conferences. As this is a role within the Applied team, candidates must be confident in their ability to move research through to production.

• Develop and iterate core models for context-aware enterprise agents, including planning, retrieval, grounding, and multi-step decision pipelines.
• Conduct research on any ML frontier relevant to agentic systems (e.g., LLMs, multimodal models, structured reasoning, data generation, or video-text modelling).
• Build robust training, evaluation, and benchmarking setups for new model variants and agent behaviours.
• Prototype new agent capabilities and work closely with engineering teams to turn them into production-quality features.
• Analyse failure modes of agents in real customer environments and design methods to improve reliability, grounding, and actionability.
• Contribute to internal research papers, technical memos, and (where appropriate) external publications.

• Currently completing or recently completed a PhD in Physics, Mathematics, Machine Learning, Computer Science, or a related field from a top university.
• Strong publication record at leading venues such as NeurIPS, ICML, ICLR, ACL, CVPR, ICCV, or EMNLP.
• Solid understanding of modern ML architectures (transformers, diffusion, retrieval-augmented systems, reinforcement learning, etc.).
• Strong coding skills in Python and experience with at least one major ML framework (PyTorch, JAX, TensorFlow).
• Ability to bridge high-level research with practical implementation.
• Curious, humble, and excited to work on hard technical problems with real enterprise impact.

• Experience in agentic or autonomous decision-making systems (not required).
• Prior work on LLM alignment, grounding, tool use, or planning.
• Experience with enterprise data environments, knowledge graphs, or retrieval systems.
• Hands-on experience with large-scale training, distributed compute, or evaluation tooling.

• Work on a high-impact ML problem space that blends deep research with real product deployment.
• Collaborate with a world-class team of scientists and engineers with prior experience at leading AI labs and tech companies.
• Opportunity to publish, attend conferences, and lead impactful research directions early in your career.
• Competitive salary, equity, and benefits.
• Located in central London with a strong in-person research culture.