We are looking for a Python Engineer (MLOps / Data Infrastructure) to help us build scalable data systems that power our machine learning models.

You will work on acquiring, structuring, and maintaining high-quality datasets from diverse sources, and ensuring their reliability and usability across the ML lifecycle – from data collection to training and evaluation.

This role is ideal for engineers who enjoy solving complex data problems and building robust infrastructure for real-world ML systems.

What You Will Do

• Design and maintain scalable data pipelines for collecting and processing large, diverse datasets.

• Transform raw, unstructured data into clean, structured, and ML-ready formats.

• Ensure data quality, consistency, and reproducibility across pipelines.

• Build systems for monitoring, validating, and debugging data workflows.

• Develop infrastructure supporting the full dataset lifecycle (collection → processing → training → evaluation).

• Collaborate with ML Engineers to deliver high-quality data for models.

• Optimize performance, scalability, and reliability of data systems.

What We Expect

• 4+ years of Python development experience.

• Strong engineering fundamentals and system design skills.

• Experience building data pipelines or data-intensive systems.

• Experience working with APIs and semi-structured data (JSON, HTML).

• Solid knowledge of SQL/NoSQL databases.

• Understanding of reliability, maintainability, and performance trade-offs.

• Ability to work autonomously and take ownership of systems.

⭐ Nice to Have:

• Experience working with data for machine learning systems.

• Familiarity with workflow orchestration tools (Airflow, Prefect).

• Experience with cloud platforms (AWS, GCP, Azure).

• Experience with containerization (Docker).

• Familiarity with data validation or versioning tools.

• Understanding of distributed systems or large-scale data processing.

What We Offer

• Work on challenging real-world data problems directly impacting ML models.

• Combine low-level data extraction with high-level ML infrastructure.

• Competitive salary and equity options.

• Flexible working environment.

• Opportunity to collaborate with top researchers, musicians, and engineers in the field.

• A dynamic startup culture with a focus on creativity and experimentation.

If you’re passionate about music, AI, and cutting-edge technology, we’d love to hear from you! Apply now and join us in shaping the future of generative audio.