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, improve tooling, and drive innovation in LLM and audio ML applications.
What You Will Do
Develop and optimize ML models focused on audio data to extract business-critical insights from previously unstructured voice data. Build agents capable of operating natively on real-world audio inputs.
Why It Might Be a Fit
Proven experience building and deploying ML models into production environments. Demonstrated ability to own the full model lifecycle from data ingestion and model development to deployment and 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.
- Excellent communication skills with the ability to engage directly with customers and stakeholders.
Benefits
- above market base
- bonus
- equity
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