Job Title: Senior Machine Learning Engineer â Embedded AI & MLOps (Quantum Sensing & NMR)
About qubiz.team: At qubiz.team, we turn cutting-edge quantum physics into commercial products. We build NV center-based sensors for biomedical and industrial use cases, and we are currently developing a pioneering portable hyperpolarized NMR platform for real-time contaminants detection.
About the Role: We are seeking a Senior Machine Learning Engineer to build the software architecture and MLOps infrastructure driving our physical platforms. Your mission will be to take AI models from research into production, optimizing them for low-latency, real-time inference and embedding them into our hardware devices and quantum sensing systems.
Key Responsibilities:
Build and maintain robust MLOps pipelines for data processing, model training, and continuous deployment onto sensing hardware.
Optimize ML/DL models for real-time, low-latency execution (edge computing / embedded systems) within our portable PFAS detector and NV sensing units.
Refactor research prototypes into clean, modular, and production-ready software suitable for industrial and medical settings.
Design data architecture and hardware-software interfaces (APIs, streaming data pipelines) for direct sensor integration.
Requirements:
PhD or Masterâs degree in Computer Science, Software Engineering, Data Science, or a related technical discipline.
5+ years of experience as an ML or MLOps Engineer deploying production-grade systems.
Expert proficiency in Python, C++ (highly desirable for hardware integration), and containerization (Docker, Kubernetes).
Proven track record in model optimization (TensorRT, ONNX, quantization) and deployment on edge or embedded environments.
Experience with MLOps frameworks (MLflow, DVC, etc.) and cloud infrastructure.
Fluent in English (C1).
What we offer:
Immediate onboarding into a pioneering scientific-technological environment with high social and environmental impact.
An interdisciplinary environment collaborating with researchers and engineers from diverse fields.
Workplace flexibility and opportunities for professional growth.
Competitive compensation commensurate with experience and responsibilities.
