Our Client, a Tier 1 VC backed startup based in New York, is looking to solve the problem of how outside sales and service teams work by revolutionizing the way they capture and analyze real-world conversations using AI technology.
Requirements
- 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.
- Proven experience building and deploying ML models into production environments.
- Experience with audio-focused ML projects or similar domains involving unstructured data.
- Familiarity with FastAPI, OpenAI APIs, Baseten, LiteLLM, LiveKit, PostgreSQL, Redis, and S3 is a plus.
Responsibilities
- Design, build, and deploy production-grade ML systems with end-to-end ownership of the model lifecyclefrom conception to deployment and maintenance.
- Architect and deliver AI-powered solutions enabling natural speech interaction and real-time audio understanding.
- 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.
- Collaborate with cross-functional teams to shape the foundations of the AI stack, improve tooling, and drive innovation in LLM and audio ML applications.
- Handle the entire AI lifecycle, including data acquisition, preprocessing, model training, deployment, inference, and monitoring in production environments.
- Participate in continuous improvement of the ML infrastructure and processes for scalability and performance.
Other
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
- 16 years of professional experience in ML engineering.
- Excellent communication skills with the ability to engage directly with customers and stakeholders.
- Work directly with customers to identify needs, gather feedback, and deliver impactful real-world solutions.
- Collaborate with cross-functional teams to shape the foundations of the AI stack, improve tooling, and drive innovation in LLM and audio ML applications.
