Vancouver/ CA
Código de referência: QUANTUM_COMPUTER_2016
Vaga Permanente

Machine Learning Researcher – Quantum computers.  PhD EE/Comp Eng/ Compsci with math/prob/stats.

Algorithms in Python/Matlab/Julia.   Vancouver./CA

Our client builds hardware with the goal of computing as fast as nature will allow.   They have been granted over 110 U.S. patents and have over 70 peer reviewed papers.  They have raised over 170 million dollars.  Their investors include Goldman Sachs and Bezos Expeditions and they are in partnerships with organizations such as Google and NASA.

They are working hard on exploiting quantum resources which are known to offer large computational speedups on some problems. They have developed a quantum annealing computer which is able to sample from probability distributions and optimize functions that are computationally intractable using classical hardware.  When viewed as a sampler, the native operation of their machine is analogous to a sparsely-connected restricted Boltzmann machine.  Similar network dynamics have fueled the recent explosion in the field of deep learning, the results of which are presently deployed in products ranging from speech recognition to image search. Their applications research team is exploiting the parallels between these architectures to substantially accelerate learning in deep, hierarchical neural networks.

The Machine Learning Researcher will work with a team of machine learning and quantum computation experts to design and implement novel machine learning algorithms that leverage the power of their quantum computer. The candidate will design and implement algorithms being developed by the team, investigate their properties, and help fine-tune their design.

This role allows inventive, ground-breaking research in an exciting and collaborative research environment. Their Machine Learning Researchers are given the freedom to work within their passions towards the overall goals, and they encourage exploration of new ideas and publication of the findings.

• Work closely with machine learning experts to design, implement, tune, and optimize machine learning algorithms.

• Design and implement experiments to test the quality of machine learning algorithms.

• Validate promising research concepts with high quality Python, Matlab, or Julia implementations.

• Apply software engineering best practice: software design patterns, version control, unit tests, documentation.

• Work with a diverse group of technical experts to incorporate their expertise into software projects.

• PhD in computer science, statistics, applied mathematics, or physics.

• Experience in statistical methods for machine learning, ideally including probabilistic models, with a focus on Boltzmann machines and MCMC techniques.

• Demonstrated success in the application of machine learning to practical problems.

• Expert coding abilities. Preference given to demonstrated experience using Python, Matlab, or Julia.

• Self-motivated, proactive and flexible with excellent problem solving skills

Candidates from any country are welcome, since they do have the required experience.