Research Artificial Intelligence Specialist

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

TRIBE - Teamwork, Respect, Integrity, Bold & Engage are our cultural cornerstone. We respect all our people and aspire to supply inclusive working experiences and an environment that reflects the audience we serve.

We are diverse, we come from different backgrounds and different countries. We are software engineers, designers, researchers, marketers, accountants, customer service, production operatives, technologists and more. We believe that a diverse organisation makes us stronger.

We are looking for talented research engineers to join our highly skilled Advanced Signal Processing and Artificial Intelligence (ASPAI) research team. In the context of digital transformation of the music equipment and audio equipment industry, together we are researching and developing the audio processing features of the future, with direct pathways to impact across the whole range of Music Tribe products.

If you have a PhD or a Master’s degree with a focus on audio processing based on deep learning or advanced signal processing (e.g. NMF, scattering transform, sparse decompositions etc.), preferably with proof of impact in terms of industry experience or an outstanding list of publications, please join our team of talented individuals! 

We look forward to talking to you soon! 

Our Purpose

We at Research Artificial Intelligence believe that delivering life-changing AI Services through self-service tools related to Machine Learning and Advanced Signal Processing will empower our?Customers as well as Music Tribe.

We further believe that relentlessly and consistently measuring and improving our services, will lead?to appreciation and Customer Advocacy.

Roles and Responsibilities

• Define and execute research strategies designed to deliver algorithms and intelligent?automation??for audio equipment products
• Research and develop intelligent algorithms and AI?solutions
• Architect efficient and scalable machine learning pipelines and associated?governance
• Create guidelines and policies relating to data set management and Machine Learning?operations
• Partner with product managers to define research projects aimed at innovating Music Tribe product?portfolio and operational?excellence.?
• Engage with partners, customers (internal and external), educational and leading-edge?technology associations to understand technology and market trends related to advanced digital signal processing, machine learning?and artificial?intelligence.?

Operations

• Implement AI Research and Development best practices

Qualifications, Minimum

• PhD or Master’s degree with a specialism in deep learning, machine learning, computer science or a related field?, and an application in music, speech or advanced signal processing, preferably with industry experience or an outstanding list of publications
• Knowledge and experience of parallel computing and GPU programming
• Experience shipping one or more projects involving AI and deep/machine Learning
• Experience in publishing literature in top-tier journals and conferences
• Experience in machine learning using tools like TensorFlow/Pytorch/Scikit-learn
• Strong system development skills, ranging from rapid research prototypes to carefully architected complex systems
• Experience in remote team work
• Global, multi-cultural, matrix organization experience
• Strategic, structured, collaborative, resilient?, good communicator 

Tools

• Tensorflow or Pytorch 
• Python, C++
• Cloud Computing 
• Git
• MS 365 Suite 

Metrics

• Algorithms and Automation Accuracy?, Adoption, Delivery and ROI

Why work for us?

• Annual leave provision, plus public holidays
• Pension / retirement fund contributions
• Health Care
• Hybrid & remote working options in some locations
• We measure our People Engagement
• We run quarterly team building events
• We are invested in learning & development
• We reward daily through digital recognition systems