ABOUT US

For over 25 years, Native Instruments has been at the forefront of sonic innovation. Guided by our mission to inspire and enable creators to express themselves, we develop integrated audio hardware and software solutions for musicians, producers, engineers, and DJs of all genres and levels of experience.
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.

OUR IDEAL CANDIDATE

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.

Please refer the Job description for details