About the Position

AI Research Scientist (PhD)

RkiveAI

Lead foundational research in event-centric temporal reasoning, multimodal representation learning, and long-horizon sequential coherence.

Remote

Posted: 2026-02-24

Full-Time

Responsibilities

You will lead foundational research in temporal and multimodal reasoning. The core challenge: models trained on next-token prediction or contrastive objectives develop strong single-frame and short-context representations, but they do not learn temporal event structure. They do not model how semantic states transition across time, what causal dependencies connect events, or how intent propagates through a sequence. These properties do not emerge reliably from scale alone - they require explicit supervision signals and representation targets designed around temporal structure.

Temporal representation architecture: Design and implement learned representations that model event boundaries, causal dependencies, and semantic state transitions as first-class objects - not implicit correlates of frame-level features.
Training on production signal: Develop training regimes that use real human editorial decisions as supervision targets. These decisions encode implicit temporal reasoning - what matters, when it matters, and why it relates to what preceded it - and are not available in standard video datasets.
Evaluation and robustness: Build evaluation harnesses that measure causal coherence and semantic consistency under distribution shift, input perturbation, and context length scaling. Benchmark against external multimodal baselines through the existing model interface.
Multimodal fusion: Develop methods for integrating visual, auditory, and textual signals into unified temporal representations, building on the existing fusion infrastructure.
Efficiency research: Investigate dynamically sparse encoding guided by learned semantic attention - computation that scales with semantic complexity, not raw sequence length.
Cross-domain generalisation: Extend temporal representations beyond the initial training domain to evaluate transfer across tasks and modalities.
Publication and disclosure: Contribute to external research communication at appropriate timing, aligned with IP and partnership strategy.

Requirements

PhD required: In computer science, machine learning, computational neuroscience, or a closely related field. Completed or defending by mid-2026.
Research focus: Strong background in one or more of: temporal modelling, sequence representation, multimodal learning, video understanding, structured prediction, event-centric reasoning, or causal inference over sequences.
Publication record: Demonstrated ability to produce and publish rigorous research. Quality and relevance over volume.
Systems intuition: You understand the gap between a research prototype and a production system. You care about closing it - and you will be joining an environment where the infrastructure to close it already exists.
First-principles thinker: You question assumptions rather than accept consensus defaults. You can articulate why current approaches to temporal coherence fail, not just what might work next.
Independent and driven: You do not need to be managed. You need to be pointed at the right problem and given the resources to solve it.
Ambitious: You want your work to matter - not just in citations, but in deployed systems used by real people.

Nice to Have

Tools: Python, PyTorch (JAX a plus), Hugging Face ecosystem, distributed training infrastructure, standard MLOps tooling.

We Offer

Fully Remote
Competitive Compensation
Rolling interviews
Performance-based cash bonuses

About the Company

Rkive is an AI lab focused on multimodal reasoning across time and complexity.

We develop novel architectures and products. We aim to create intelligent environments that work alongside you - proactively, reliably, and responsive to intent.

Meaningful work: What we are building is genuinely unprecedented. The problems are hard and the opportunity is enormous.
Autonomy: Fully remote. Manage your own time. Take time off when you need it.
Zero politics: No bureaucracy, no posturing, no performative culture. Just the work.
Mutual respect: We back our people, but we expect the same in return.
Honest environment: Not a family, not a pressure cooker. A high-trust, high-performance team.

Apply

If this is the kind of problem you have been waiting to work on, we want to hear from you.

Send your CV and research materials to [email protected]

Apply now

AI Research Scientist (PhD)

Job description