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Multimodal AI Researcher - PhD / Machine Learning / Python / C++

European Tech Recruit
Manchester
5 months ago
Applications closed

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Multimodal AI Researcher - PhD / Machine Learning / Python / C++


We're searching for a Multimodal AI Researcher to join out client on an initial 6 month contract working on a hybrid model in Surrey.


This is a 6 month contract that would suit either a PhD student looking for an internship or a PhD graduate seeking a 6 month contract.


As a Multimodal AI Researcher, you will:

  • Drive innovation by developing cutting-edge solutions to real-world problems in on-device audio-visual AI.
  • Proactively propose and prototype novel research ideas, factoring in practical constraints.
  • Contribute to the development of complex AI systems, transforming research concepts into production-ready software.
  • Apply software engineering best practices across both research and development phases.
  • Effectively communicate research findings through technical reports and/or academic publications.



Required skills:

  • Recent graduate or currently pursuing a Ph.D. in Machine Learning/AI, Computer Science/Engineering, Mathematics, Statistics, or a related field.
  • Strong foundational knowledge in machine learning and artificial intelligence.
  • First-author publications in top-tier ML/AI conferences or journals (e.g., CVPR, ICCV, NeurIPS, ICML, ICLR, ICASSP, INTERSPEECH, IEEE TPAMI, IEEE IoT, IEEE TNNLS, JMLR, or similar).
  • Hands-on machine learning experience in at least one of the following areas:
  • Multimodal LLMs (audio and/or video)
  • Contrastive learning (e.g., multimodal feature alignment)
  • Model compression techniques (e.g., quantization, pruning, knowledge distillation)
  • Proven success in:
  • Software development using Python and/or C/C++
  • Working with ML frameworks such as PyTorch and/or TensorFlow
  • Writing clear and thorough documentation
  • Using standard software engineering tools and practices (e.g., Git)
  • Strong communication and collaboration skills with a results-driven mindset
  • Excellent problem-solving and debugging abilities


Preferred skills:

  • Background in multimodal emotion recognition and foundational facial models
  • Experience with multi-task learning and deception detection
  • Demonstrated ability to build sophisticated training and inference pipelines
  • Knowledge of embedded and/or distributed ML tools and methodologies
  • Experience in optimizing and profiling AI pipelines for performance
  • Contributions to open-source machine learning libraries


If this sounds interesting and you'd like to learn more, click the link below to apply or email me with a copy of your CV on


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