Our Client is a rapidly growing Tier 1 VC backed startup based in New York with $60 million in funding revolutionizing how outside sales and service teams work. Their AI technology captures and analyzes real-world conversations, providing full visibility into every customer interaction without the need for traditional ride-alongs. By turning field conversations into searchable, actionable data, they empower teams to coach more effectively, close more deals, and boost average ticket sizes. Combining cutting-edge AI with a deep understanding of field sales dynamics, this company is redefining how businesses learn from and optimize their in-person customer experiences.
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.
- Demonstrated ability to own the full model lifecyclefrom data ingestion and model development to deployment and monitoring.
- Experience with audio-focused ML projects or similar domains involving unstructured data.
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
- Work directly with customers to identify needs, gather feedback, and deliver impactful real-world solutions.
- Excellent communication skills with the ability to engage directly with customers and stakeholders.
- 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.
