Senior Machine Learning Engineer

un:hurd music; London; Hybrid; GBP 70,000 - 130,000; Full time

Job summary

A leading music-tech company is seeking a skilled ML Engineer to enhance their AI capabilities. You will be responsible for building and deploying machine learning models to revolutionize marketing for independent artists. This senior role involves hands-on data work, cross-functional collaboration, and project management in a dynamic environment. Benefits include equity options, dedicated training, and remote work flexibility.

Benefits

EMI share options

Dedicated training days every month

Support for career growth

25 days annual leave + paid bank holidays

Benefits package

Qualifications

• 3+ years in machine learning with impact.
• Programming skills in Python and distributed computing libraries.
• Experience deploying ML models using cloud platforms.

Responsibilities

• Own deployment and maintenance of ML models.
• Develop efficient data pipelines from APIs.
• Optimize data management and storage for scalable processing.

Skills

Machine Learning

Data Engineering

Python

MLOps

PySpark

Cloud Computing

CI/CD

Communication

Education

Master's degree in a quantitative discipline

Tools

Azure ML

PyTorch

TensorFlow

Docker

Kubernetes

Git

Job description

Direct message the job poster from un:hurd music

Lead Data Scientist at Un:hurd Music, PhD

Who We Are

For years, artists have been 'shooting in the dark' when it comes to their marketing. There's a clear lack of robust, transparent and accessible marketing tools for musicians and artists to use to promote their music.

At un:hurd music, we've created a music-tech platform that uses proprietary technology to turn music data into stronger promotional campaigns for artists. We've created both mobile and web applications which act as the 'digital marketing companion' for independent artists, facilitating data-led promotional campaigns across streaming and social media platforms.

Over the past two years we’ve reached some milestones we’re really proud of, including:

• Featured on BBC’s Dragons Den
• Raising money from the world's leading Music-Tech investors
• Being listed as one of Music Ally’s ‘start-ups to watch’
• Being voted as a Music Ally si:x start-up finalist
• AIM and Great British Entrepreneur of the year nominee
• Winning the Antler x ADE start-up competition
• Participants in the Marathon Music, Wallifornia and BPI x Mayor Of London’s GROW Accelerator programs
• Helped over 155,000 artists and record labels reach their goals.

Values that we live by

• We put artists first at all times.
• We are tenacious, hard-working and go the extra mile.
• We push the boundaries and challenge the status quo.
• We are solutions focused and have a ‘can do’ attitude to problem solving.
• We are fair, loyal and great to work with.
• We encourage everyone to take responsibility and to be accountable.

The Role

We're expanding our small and talented team and looking for a dedicated, proactive, and diligent ML Engineer to grow with us and enhance our ML and AI capabilities. This role will be a senior hire responsible for the software development and technical infrastructure needed to design, train, deploy and scale machine learning models in production environments. You will harness a diverse array of data sources, from streaming services to social media, revolutionizing the way artists promote their music.

Our Data Team members are full stack data professionals who independently manage projects across the complete spectrum, from raw data ingestion to deployment, monitoring, and optimization. While this role emphasizes data engineering and ML deployment, you will have the responsibility of managing projects with autonomy across the full data lifecycle.

Responsibilities

As an ML Engineer at Un:hurd music, you'll be:

• MLOps and Model Deployment: Own the deployment, maintenance, and retraining of machine learning models in production environments, designing scalable system architectures to ensure performance and resilience.
• Data Collection and Integration: Develop and integrate efficient data pipelines by collecting high-quality, consistent data from external APIs and ensuring seamless incorporation into existing systems.
• Big Data Management and Storage: Utilize PySpark for scalable processing of large datasets, implementing best practices for distributed computing. Optimize data storage and querying within a data lake environment to enhance accessibility and performance.
• ML R&D: Collaborate on model prototyping and development, identifying the most relevant and efficient solutions to the core problems that artists face. This involves deep research, hands-on experimentation, and iterative development to create, refine, and optimize models, prior to full-scale deployment.
• Cross-Functional Collaboration: Working with business stakeholders, product managers, and engineers to translate business goals into actionable solutions, and communicating results clearly to both technical and non-technical stakeholders.

Essential Experience

• 3+ years of experience in applying machine learning in a commercial setting, with a track record of delivering impactful results.
• Extensive programming skills in Python, with a specialization in distributed computing libraries such as PySpark.
• Extensive experience with PyTorch (preferred) and/or TensorFlow.
• Hands-on experience with deploying machine learning models in production using cloud platforms, especially Microsoft Azure ML / Databricks ML Flow.
• Experience in integrating CI/CD pipelines for ML models.
• A proactive, hands-on approach to building, iterating, and owning solutions end-to-end.
• Strong interest in machine learning and data engineering, with an eagerness to stay up to date on evolving tools and practices.
• Strong communication skills to effectively tailor messaging to both technical and non-technical stakeholders.
• Proven ability to lead projects independently.
• Responsible, collaborative and team oriented.
• Experience working with software development teams.

Preferred Experience

• A master’s degree in a quantitative discipline such as data science, statistics, software engineering, or computer science.
• Familiarity with Azure functions.
• Familiarity with infrastructure-as-code tools (e.g., CloudFormation, Terraform).
• Experience with Docker/Kubernetes.
• Experience with explainability tools and ensuring model transparency and compliance in real-world deployments.
• A strong working understanding of Git version control and workflow.
• Having worked in a startup environment would be a plus.

Benefits

• EMI share options.
• Dedicated training days every month.
• Support to help grow your career.
• 25 days annual leave + paid bank holidays.
• Benefits package

Location: Our ideal candidate will work in a hybrid setup in our office, but we are open to fully remote applicants. We have an office in London at Tileyard creative industries hub should you use that space. Our team is spread across the UK, we meet regularly via video calls and at least quarterly meet at our London office - if you are required to travel we will cover all costs.

A successful application will lead to:

• An initial conversation to get to know each other and assess your fit for the role
• A technical interview which will include a technical task to complete with some preparation, and follow-up questions.
• A last stage call with our CEO.

If you have a disability, please let us know if there's any way we can make the interview process better for you; we're happy to accommodate.

un:hurd music is made up of people from a variety of backgrounds and lifestyles. We embrace diversity and invite applications from people of all walks of life. We don't discriminate against employees or applicants based on gender identity or expression, sexual orientation, race, religion, age, national origin, disability, pregnancy status or any other differences.

All applicants must have the right to work in the UK. We are unable to offer sponsorship.

www.unhurdmusic.com

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  Music

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