Full-Time Senior Research Engineer
Output is hiring a remote Full-Time Senior Research Engineer. The career level for this job opening is Senior Manager and is accepting USA based applicants remotely. Read complete job description before applying.
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Love music? Come sit with us. We help creative people make better music with cutting-edge technology.
Output is a global leader in music creation software.
We build tools that push the boundaries of musical creativity.
Our R&D team is growing, and we're looking for a Senior Research Engineer to join us in creating innovative new AI-based music creation products.
In this role you will rapidly prototype new ideas applying the latest technologies, developing, training, refining, and deploying ML-based models for exciting new features.
This role will work on prototyping features in areas including search, audio analysis, generative audio, and more.
The ideal candidate is intrinsically motivated, detail-oriented, and energized to contribute to the future of our R&D roadmap.
How you'll add value:
- Develop, build, and test ML models with a small R&D team.
- Determine the best approach and application of ML technology.
- Apply modern ML frameworks and tools.
Collaboration and communication:
- Participate in discussions with stakeholders to understand and develop requirements.
- Work with software engineers, content specialists, QA, and other team members.
Optimization and iteration:
- Data analysis and measuring model performance.
- Continuously optimize ML models for performance and accuracy.
- Tune hyperparameters, curate datasets, and optimize algorithms.
Skills Required:
- 5+ years experience in applied research in AI/ML.
- MS or PhD in CS, ML, or equivalent.
- Interest and passion in music tech.
- Strong problem-solving skills.
- Experience developing prototypes and tests.
- Experience with specific ML tools (Python, Numpy, Pytorch, Tensorflow, Pandas).
- Training, evaluating, and fine-tuning open source models.
- Familiarity with modern ML models.
- Understanding of audio signal processing.
- Knowledge of music theory.
- Experiment Tracking Frameworks (Neptune, W&B).
- Deployment of models.
- Experience with digital audio workstation software and AI-based music production workflows.