Machine learning engineer

Job Description:

I am partnered with a leading developer and provider of full-stack photonic quantum computing systems. This company focuses on innovative approaches to quantum computing, high performance, and data centre-standard systems for machine learning and generative AI. You will have the opportunity to work in multidisciplinary teams of quantum scientists’, engineers, and mathematicians who are developing hardware and software within quantum- classical systems.

We're looking for an experience machine learning engineer, who will thrive in collaborative dynamic environments where learning is continuous and every contribution drives progress towards the next generation of computing. Having knowledge or interest within quantum computing would be desirable.

Your Responsibilities:

• You will research, implement and benchmark new machine learning algorithms to continuously improve your workflows.
• You will focus on generative models (flow models, diffusion and GANs), alongside neural network architectures that make use of non-classical feature sets.
• You'll be working in collaboration with clients and partners mapping relevant problems within hardware and deliver projects demonstrating how your technology can solve these problems.
• Country to scientific leadership by publishing your research and working with legal teams to protect your inventions.
• You will contribute to the user facing software stack by adding and improving new algorithm applications and examples.

Technical Expertise:

• Master's or PhD in a relevant field (physics, computer science...)
• Expertise in machine learning, with a strong understanding of flow matching, diffusion and/ or GANs
• Machine learning orientated programmed skills (Pytorch, Python…)
• Experience in developing and benchmarking new machine learning models
• Working with multi-GPU models
• Industrial experience in machine learning applications for either chemistry or biology settings
• Experience working in front of and with customers
• Previous experience working in start-up environments

Following your application, Amelia Pudney will discuss the opportunity with you in detail. She will happily answer any queries surrounding the opportunity and the potential for career growth. This position is highly popular and has possibility to close prematurely; apply as soon as possible to avoid disappointment.

Please select 'apply', alternatively email [email protected] with any further information.

I am partnered with a leading developer and provider of full-stack photonic quantum computing systems. This company focuses on innovative approaches to quantum computing, high performance, and data centre-standard systems for machine learning and generative AI. You will have the opportunity to work in multidisciplinary teams of quantum scientists’, engineers, and mathematicians who are developing hardware and software within quantum- classical systems.

We're looking for an experience machine learning engineer, who will thrive in collaborative dynamic environments where learning is continuous and every contribution drives progress towards the next generation of computing. Having knowledge or interest within quantum computing would be desirable.

Your Responsibilities:

• You will research, implement and benchmark new machine learning algorithms to continuously improve your workflows.
• You will focus on generative models (flow models, diffusion and GANs), alongside neural network architectures that make use of non-classical feature sets.
• You'll be working in collaboration with clients and partners mapping relevant problems within hardware and deliver projects demonstrating how your technology can solve these problems.
• Country to scientific leadership by publishing your research and working with legal teams to protect your inventions.
• You will contribute to the user facing software stack by adding and improving new algorithm applications and examples.

Technical Expertise:

• Master's or PhD in a relevant field (physics, computer science...)
• Expertise in machine learning, with a strong understanding of flow matching, diffusion and/ or GANs
• Machine learning orientated programmed skills (Pytorch, Python…)
• Experience in developing and benchmarking new machine learning models
• Working with multi-GPU models
• Industrial experience in machine learning applications for either chemistry or biology settings
• Experience working in front of and with customers
• Previous experience working in start-up environments

Following your application, Amelia Pudney will discuss the opportunity with you in detail. She will happily answer any queries surrounding the opportunity and the potential for career growth. This position is highly popular and has possibility to close prematurely; apply as soon as possible to avoid disappointment.

Please select 'apply', alternatively email [email protected] with any further information.