Data Engineer for Audio ML Research
- 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.
- 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.
- Remote First: We offer a range of options that allow you to work in a way that suits your lifestyle, either at one of our workspaces, a hybrid arrangement, or fully remote.
- Shared workspace in London: Landmark Spaces
- Workation: Work remotely anywhere in the world for up to 4 weeks per year
- Flexible work model from one of our entity locations
- Trust-based working hours
- Holidays: 25 days paid holiday per year which increases with tenure
- Healthcare: Public health care with NHS supplemented with Simply Health. This involves contributions for dental and optical healthcare, for example
- Pension: Employees can choose an auto enrolment scheme or can bring their own SIPP with them
- Free software downloads and reduced prices on hardware
- Employee Assistance Program for your well-being
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