Salary – Competitive Salary + Excellent Benefits
Our client is a leading company that develops cutting-edge artificial intelligence solutions for major global and local clients in Europe, Middle East and Africa. They focus on developing enterprise software solutions that solve existing problems across a range of industries using advanced machine learning, deep learning and deep reinforcement learning. Their expertise spans across research, development, visualisation, and design, allowing the whole end-to-end solution to be developed in-house across our teams in London, Paris, Tunis, Lagos, Cape Town and Dubai.
Our client is looking for a new Research Engineer in Reinforcement Learning to join their expanding Research team in London. The team is primarily focussed on fundamental research with a particular emphasis on Reinforcement Learning and decision-making. Research efforts are towards developing novel algorithms and improving the state-of-the-art in performance.
In the Research team, the focus of a Research Engineer is to support the research effort through the development and implementation of novel ideas, whilst building effective, modular and sustainable software solutions. The core tasks Research Engineers are responsible for include: developing prototype applications, providing software design and programming support to research projects, as well as implementing and maintaining software libraries.
Given the current state of the pandemic, all work will be fully remote. However, relocation may be required once the situation improves. In this role you will report to the AI Research Lead.
Implement novel algorithms and research ideas as directed by Research Scientists and team leads in accordance with the team’s research agenda and goals. This will primarily be in the area of Reinforcement Learning, but could include related algorithms/ideas spanning larger fields such as machine learning and deep learning in general.
Contribute to the design, project planning and implementation of a core research library and environment test suite for Reinforcement Learning.
Design and implement algorithms in such a way to best leverage modern hardware and distributed computing systems (CPUs, GPUs, TPUs, Cloud, etc.).
Report and present experimental results and research findings clearly and effectively, both internally and externally, verbally and in writing.
Contribute to the team’s publication efforts, which could include the development of model diagrams, producing high quality plots of experimental results, assisting in writing up experimental details and results.
When required, bridge the gap between the research and product teams by integrating new fundamental research into applied projects. This could include collaborating with the Engineering team to design and run experiments, including designing and evaluating new algorithms as well as implementing known algorithms at scale across distributed computing infrastructure and assist in deploying models in production.
Upon request, collaborate with the business development team in their pre-sales activities, including but not limited to presenting the company to new prospective clients, writing decks and proposals, participating in calls and meetings, and representing the company at conferences/events.
M.S./Ph.D. degree in Computer Science, Operations Research, Reinforcement Learning or related fields.
Experience in developing and debugging in C/C++, Python or similar languages.
Experience using deep learning frameworks such as PyTorch, Tensorflow and/or Jax.
Experience with distributed systems, HPC, compilers, and/or CUDA programming.
Research and software engineer experience demonstrated via an internship, contributions to open source, work experience or coding competitions.
Proven ability to contribute to research communities and/or efforts, including publishing scientific papers at conferences (JMLR, ICLR, NeurIPS, ICML, GECCO, etc.).
Work permit for UK.
Working in small, diverse teams where you can make an impact.
Varied challenges across industries .
Annual offsite events.
Flexible working hours.
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