On-Device Machine Learning Engineer
About Us:
webAI is pioneering the future of artificial intelligence by establishing the first distributed AI infrastructure dedicated to personalized AI. We recognize the evolving demands of a data-driven society for scalability and flexibility, and we firmly believe that the future of AI lies in distributed processing at the edge, bringing computation closer to the source of data generation. Our mission is to build a future where a company's valuable data and intellectual property remain entirely private, enabling the deployment of large-scale AI models directly on standard consumer hardware without compromising the information embedded within those models. We are developing an end-to-end platform that is secure, scalable, and fully under the control of our users, empowering enterprises with AI that understands their unique business. We are a team driven by truth, ownership, tenacity, and humility, and we seek individuals who resonate with these core values and are passionate about shaping the next generation of AI.
About the Role
We’re looking for an On-Device Machine Learning Engineer to bring modern ML capabilities directly onto consumer hardware, specifically fast, private, and reliable. You’ll own the design, optimization, and lifecycle of models running locally (e.g., iPhone/iPad/Mac-class devices), with a sharp focus on latency, battery, thermal behavior, and real-world UX. This role sits at the intersection of ML systems, product engineering, and performance tuning, and will help power local RAG, memory, and personalized experiences without relying on the network.
What You’ll Do
On-device model optimization and deployment
- Convert, optimize, and deploy models to run efficiently on-device using Core ML and/or MLX.
- Implement quantization strategies (e.g., 8-bit / 4-bit where applicable), compression, pruning, distillation, and other techniques to meet performance targets.
- Profile and improve model execution across compute backends (CPU/GPU/...