Machine Learning Researcher - London

<p>As a Machine Learning Engineer, you will take the lead on optimising the functionality, performance, and algorithmic engineering powering our machine learning models. This is a critical role for a hands-on expert who can deliver state of the art models, set the standard for performance, and ensure our models are accurate, robust, efficient and scalable.</p><br>Are you the right candidate for this opportunity Make sure to read the full description below.<br><p><strong>What you’ll do: </strong></p><ul><li>Lead the development and refinement of novel machine learning architectures and algorithms harnessing our nonlinear dynamics. Building deeper network architectures that maximise efficiency and performance.</li><li>Design, build and test models both on device and using in-house simulation framework.</li><li>Collaborate closely with the wider photonics and hardware team to design and evaluate general metrics to assess the computational properties of the hardware and optimise for computational performance. xwzovoh </li><li>Research state-of-the-art machine learning & machine vision techniques and adapt them to be compatible with our hardware.</li></ul><p><br></p><ul><li><strong>Experience:</strong></li><li>Proven track record of developing novel algorithms (papers in NeurIPS, ICML, ICLR, CVPR, or Nature/Science journals)</li><li>Hardware Aware ML / Neuromorphic Computing:</li><li>FPGAs, ASICs, analog computing chips, spiking neural network (hardware), edge AI</li><li>Unconventional training algorithms</li><li>Reservoir computing, self-constrastive learning, forward-forward learning, evolutionary algorithms, equilibrium propagation</li><li>Physics informed neural networks, or applied ML to physics problems</li><li>Deep understanding of mathematics, algebra / topology - key words are latent space, intrinsic dimensionality</li><li>Experience working with hardware as well is a bonus</li></ul>