Python Job: ML Researcher

Job added on

Company

Barclays

Location

London, England - United Kingdom

Job type

Full-Time

Python Job Details

Machine Learning (ML) Researcher
London

As a Barclays Machine Leaning (ML) Researcher, you will have the opportunity to work on the latest software and hardware frameworks around Machine Learning, Neural Networks, High Performance Computing, next generation AI silicon accelerators, Quantum computing frameworks. This is an R&D role having as main deliverable Barclays position papers (published internally or externally) around the various technologies of the market.

Barclays is one of the world's largest and most respected financial institutions, with 329 years of success, quality and innovation behind us. We offer careers that provide endless opportunity – helping millions of individuals and businesses thrive, and creating financial and digital solutions that the world now takes for granted

Working Flexibly

We’re committed to providing a supportive and inclusive culture and environment for you to work in. This environment recognizes and supports ways to balance your personal needs, alongside the professional needs of our business. Providing the opportunity for all our employees, globally to work flexibly empowers each of us to work in a way that suits our lives as well as enabling us to better service our customers’ and clients’ needs. Whether you have family commitments or you’re a carer, or whether you need study time or wish to pursue personal interests, our approach to working flexibly is designed to help you balance your life. If you would like some flexibility, then please discuss this with the hiring manager, and your request will be reviewed subject to business needs.

We are currently in the early stages of implementing a hybrid working environment, which means that many colleagues spend part of their working hours at home and part in the office, depending on the nature of the role they are in. We’re flexible on how this works and it may continue to change and evolve. Depending on your team, typically this means that colleagues spend a minimum of between 20% to 60% of their time in the office, which could be over a week, a month or a quarter. However, some colleagues may choose to spend more time in the office over a typical period than their role type requires. We also have a flexible working process where, subject to business needs, all colleagues globally are able to request work patterns to reflect their personal circumstances. Please discuss the detail of the working pattern options for the role with the hiring manager.

What will you be doing?
• Benchmarking the various technologies in short time scales (e.g. 1 month max per tech)
  • Writing reports and papers around these technologies (for internal consumption or external publication)
  • Benchmarking next generation ML platforms for internal adoption
  • Creating prototypes and pipelines for new ML use cases e.g. templates to help new teams start working on a given project
  • Delivering internal workshops on the various new technologies
  • Interacting with vendors for technical due diligence of their product

What we’re looking for:
• Excellent mathematical background e.g. optimisation, statistics, Monte Carlo, partial differential equations
  • Good programming skills in Python
  • Very good understanding of ML/ AI with a particular emphasis around deep neural networks
  • Ability to fast prototype simulating a use case in any programming framework (e.g. Python, R, Have, C, C++, Ruby, MatLab, Mathematica etc.)

Skills that will help you in the role:
• Experience with distributed ML frameworks Spark, Dask
  • Experience with at least one of the cloud ML frameworks (e.g. in AWS, Azure, Google).
  • Basic SQL knowledge
  • Experience with CUDA

Where will you be working?
In the heart of Canary Wharf, our headquarters at Churchill Place boasts onsite amenities such as; a gym, staff restaurant and deli bar, and is easily accessible by tube and bus links. With a population of around 5000 staff the atmosphere is second to none with a real buzz being created around the offices within.


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