Machine Learning & Audio Scientist

Tech Kings Cross, London Req. UMG-5875


Description



Job title:
Machine Learning & Audio Scientist
Responsible to: Sr. Director, Machine Learning & Audio
Department: Music & Audio Machine Learning Lab
Location of work: 4 Pancras Square, Kings Cross / Remote
  

Music is Universal

  

It’s the passionate and dedicated team at Universal Music UK who help make us Britain’s leading music company. From A&R to finance, legal to digital, sales to marketing, Universal Music is the place to grow and develop your career within a truly commercial and innovative business that leads in everything it does.

Everyone is welcome to apply for our roles, and we are determined to ensure that no applicant or employee receives less favourable treatment because of gender, race, disability, sexual orientation, religion, belief, age, marital status, background, pregnancy or caring responsibilities. We also recognise the importance of diversity of thought within our teams and are fully committed to embracing the talents of people with autism, dyslexia, ADHD and other forms of neurocognitive variation.

We will always seek to make appropriate adjustments to recruitment, workplaces, and work processes to be fully inclusive to people with different needs and working styles. If you need us to make any reasonable adjustments for you from application onwards, including alternatives to the online form or to disclose a neurocognitive condition, please email [email protected] 

 

The A Side: A Day in The Life

This role sits within the Music and Audio Machine Learning Lab (MAML) at UMG. The MAML’s mission is to support and empower UMG business units and partners with advanced technologies for Music, Audio and Machine Learning.

The MAML covers the full research & development lifecycle, from explorative research to prototypes to industrial scale products. It typically undertakes projects with applications such as, but not limited to, analysis and description of recordings, creative tools, search, recommendation, playlisting, auto-tagging etc.

As an Audio & Machine Learning Scientist, you will:

 

  • Design and build state-of-the-art Audio and Machine Learning algorithms to tackle a variety of tasks
  • Explore cutting-edge research in ML/MIR/Audio and new application avenues for UMG
  • Collaborate with the team and stakeholders to deploy models to production
  • Communicate results and findings to audiences of all levels of expertise
  • Be part of an innovative and dynamic team

   

The B Side: Skills & Experience

 

Necessary

  • Background in Music Information Retrieval / Machine Learning / Audio Signal Processing
  • Solid experience as a scientist e.g. PhD and 1+ years, or equivalent experience
  • Up to date knowledge of general Machine Learning / Deep Learning state of the art
  • Strong software engineering
  • Thorough knowledge of Python and usual scientific libraries e.g. Numpy, Scipy, sklearn or similar
  • Comprehensive knowledge and experience of Deep Learning and its usual frameworks (Tensorflow, Keras, Pytorch or similar)
  • Familiarity with Linux environments
  • Ability to write good, well documented, and reusable code

 
Desirable
 

  • Track record of publication(s) in relevant conferences or journals (e.g. ISMIR, ICASSP, ICML, ICLR or similar)
  • Experience in MIR tasks such as auto-tagging, music classification, structural segmentation, tempo estimation, or related tasks
  • Experience with generative models
  • Experience working in the industry
  • Experience going all the way from ideation / early research to production
  • Familiarity/experience with cloud computing environments (e.g. AWS, Google Cloud Platform or similar)
  • Experience with containerised software development (Docker)

  

Person Specification

 

  • Good communication skills, both oral and written
  • Curious, self-motivated, and proactive
  • Passion for music and/or deep musical understanding

 

If you are excited at the idea of working on state-of-the-art music & audio machine learning at industry scale and make an impact, we want to hear from you!

  

Bonus Tracks: Your Benefits

 

  • Group Personal Pension Scheme (between 3% and 9%)
  • Private Medical Insurance
  • 25 paid days of annual leave
  • Interest Free Season Ticket Loan
  • Holiday Purchase scheme
  • Dental and Travel Insurance options
  • Cycle to Work Scheme
  • Salary Sacrifice Cars
  • Subsidised Gym Membership
  • Employee Discounts (Reward Gateway)

 

Just So You Know…

 

The company presents this job description as a guide to the major areas and duties for which the jobholder is accountable.  However, the business operates in an environment that demands change and the jobholder's specific responsibilities and activities will vary and develop. Therefore, the job description should be seen as indicative and not as a permanent, definitive and exhaustive statement.