Senior Applied Researcher
About The Position
Want to build vision-language models that understand complex, real-world environments? You’ll join a small, highly technical team working on foundational problems in multimodal AI, focused on training models that can interpret, reason, and act on large-scale first-person video data. You’ll work directly with the Chief Science Officer, shaping how models are designed, trained, and evaluated. The work sits at the intersection of VLMs, long-context reasoning, and real-world deployment. The focus is on building systems that move beyond static perception, towards temporal understanding, activity recognition, and higher-level reasoning across dynamic environments.
Requirements
- strong experience training deep learning models, ideally transformer-based
- hands-on work in vision, language, or multimodal systems
- Experience with large datasets, model optimisation, or deploying models into production environments will be valuable
- Exposure to video data or long-context modelling is particularly relevant
Responsibilities
- Designing and training VLMs on large-scale video datasets
- Developing post-training approaches including SFT, RLHF, and parameter-efficient tuning
- Building scalable training and evaluation pipelines
- Exploring long-context and temporal modelling
- Designing efficient systems across edge and server-side inference
- Defining benchmarks for spatial and behavioural understanding
Benefits
- Highly competitive salary + equity
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
