Overview Data Engineer for Audio ML Research role at Native Instruments. You will join the Research team, partnering closely with Product, Design, and Engineering teams across Native Instruments brands. As our Data Engineer, you will build and operate the pipelines and datasets that make high-quality audio and symbolic audio available for experimentation and shipped products, while keeping data secure and compliant. The role is based in our Madrid hub, collaborating daily with colleagues in Boston, Berlin, and London.
Native Instruments embraces diversity and a respect for all people. We are proud to be an equal opportunity employer and we believe the foundation of our dynamic and pioneering spirit starts with a fair and inclusive culture. At Native Instruments we value teamwork and passion, delivering inspiring experiences, continuously innovating and empowering our communities, while also serving our planet.
All applicants will receive equal consideration for employment at Native Instruments and we encourage everyone to apply – regardless of gender identity, race, color, religion, sex, sexual orientation, national origin, genetics, disability, age, or any other characteristic protected by law.
Help us reach our goal in making the future of music diverse, inclusive and exciting! We encourage you to submit your application without the requirement for a photograph, identifying factors or personal status information.
Responsibilities Own Data Governance: Design and implement clear schemas, access controls, and governance to keep our audio data secure, compliant, and discoverable.
Build the Foundation: Design and run scalable data pipelines on AWS to ingest vast internal audio libraries and generate novel training data by programmatically controlling our virtual instruments and effects.
Shape the Sound: Actively curate and shape the sonic character of our datasets through expert processing, augmentation, and quality validation, directly influencing the output of our ML models.
Enable Reproducibility: Publish versioned, documented, and traceable datasets to empower reproducible research and improve team efficiency with self-serve tools and robust monitoring.
Connect to Customers: Develop pipelines that translate anonymized product telemetry into actionable insights on how our models perform in the wild.
Qualifications We are looking for a candidate who combines a rigorous data engineering background with a genuine passion for the nuances of musical audio. You understand that data quality is paramount and are eager to build datasets for creative AI.
Significant years of data engineering experience with expertise in data governance, including schema design, access controls, and compliance management.
Strong proficiency in Python and SQL.
Hands-on expertise building and maintaining scalable data pipelines on AWS, particularly using S3 and running Python jobs in containers or on Linux nodes.
A good working knowledge of audio datasets, including concepts like sampling rates, formats, and quality measures (e.g., S / N ratio, THD).
Hands-on experience with music production tools and comfort in automating VSTs, instruments, or synthesizers to generate audio.
Experience with data-centric MLOps practices like dataset versioning, experiment tracking, and data validation for ML reproducibility.
A background in data processing and augmentation for machine learning; experience with MIDI or audio feature extraction is a significant plus.
A clear and collaborative communicator, capable of partnering effectively with cross-functional teams.
A genuine love of music and audio production and enthusiasm for building the future of creative tools.
Benefits Flexible work model from one of our entity locations
Trust-based working hours
Holidays: 25 days paid holiday per year
Global Travel Insurance coverage
Public Health, Pension & Disability Insurance coverage
Free software downloads and reduced prices on hardware
Senioritу level Not Applicable
Employment type Full-time
Job function Research and Engineering
Industries Software Development
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