Role OverviewDesign, build, and deploy production-grade ML systems with end-to-end ownership of the model lifecycle. Collaborate with cross-functional teams to shape the foundations of the AI stack and drive innovation in LLM and audio ML applications.
What You Will Do
Develop and optimize ML models focused on audio data, build agents capable of operating natively on real-world audio inputs, and handle the entire AI lifecycle, including data acquisition, preprocessing, model training, deployment, inference, and monitoring.
Why It Might Be a Fit
Proven experience building and deploying ML models into production environments, demonstrated ability to own the full model lifecycle, and strong understanding of data pipeline design, real-time inference, and model monitoring.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field
- 1-6 years of professional experience in ML engineering
- Strong programming skills in Python (TypeScript experience is a plus)
- Hands-on experience with ML frameworks such as PyTorch or TensorFlow
- Familiarity with cloud environments and infrastructure (preferably AWS)
- Strong understanding of data pipeline design, real-time inference, and model monitoring
Benefits
- above market base
- bonus
- equity
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