Role OverviewThe ML Engineer will design, build, and deploy production-grade ML systems with end-to-end ownership of the model lifecycle. They will architect and deliver AI-powered solutions enabling natural speech interaction and real-time audio understanding. The role requires collaboration 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
The ML Engineer will handle the entire AI lifecycle, including data acquisition, preprocessing, model training, deployment, inference, and monitoring in production environments. They will also participate in continuous improvement of the ML infrastructure and processes for scalability and performance.
Why It Might Be a Fit
The ideal candidate will have a strong understanding of data pipeline design, real-time inference, and model monitoring. They will also have excellent communication skills with the ability to engage directly with customers and stakeholders.
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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