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Modelling Resident

Adaption· Modelling
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RemoteContractPosted 4mo ago

About the role

A modelling residency embedded in production and research projects, mentored by the modelling team. An 8-month remote contract position focused on frontier innovation in efficiency, gradient-free exploration, real-time learning, and interface design.

Responsibilities

  • Innovation: Build the future of adaptive algorithms that continuously learn. Co-design algorithms that react in real-time to product signal and feedback, and explore new ways of capturing feedback that make those algorithms better
  • Cross-Stack Optimization: Collaborate across software, hardware, and algorithmic domains to drive system-wide efficiency gains
  • Measure What Matters: Real-world impact and product signal as the measure of value; ensure algorithms can interact with the world and leverage real-world feedback

Qualifications

  • A degree or equivalent research/engineering experience in a computer science field.
  • Genuine interest in, and at least one project touching: model efficiency, synthetic data, interfaces, real-time alignment, or algorithmic optimization
  • Systems thinking — the ability to understand and optimize across the full ML stack
  • Strong Python skills and experience with deep learning frameworks (PyTorch, JAX, or TensorFlow)
  • Familiarity with model optimization techniques such as RLHF and fine-tuning
  • Strong communication and self-awareness — you know how to collaborate in a remote environment and you're open to feedback
  • You care about technical excellence and last mile impact. We value impact more than effort, and about owning outcomes end to end.

Skills

Required:PythonDeep learning frameworks
Nice to have:Model optimization techniques
Last updated Sep 10, 2026. Interested? Apply on the company site.
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About Adaption

Everything intelligent adapts. So should AI.

Adaptive DataAdaptive IntelligenceAdaptive InterfacesproductAI that adaptsAI that learnson-the-fly malleable datasetscontinual learning
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