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

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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