Overview
As a Senior ML Engineer in the intelligent AV pod, you will be responsible for evaluating, integrating, and optimizing state-of-the-art machine learning models that power the perception and awareness engine behind Q-SYS VisionSuite.
This position emphasizes strong engineering execution: systematically benchmarking external and internal models, selecting the right techniques for production constraints, and ensuring robust deployment in real-time, resource-constrained AV environments. You will work closely with ML, Robotics, and Software Engineers to advance VisionSuite as a reliable, maintainable, and high-performance solution for smart meeting spaces and intelligent buildings. This position is based in Zurich, Switzerland (hybrid).
Your mindset
* Engineering-First ML Practitioner: You prioritize robustness, reliability, and maintainability over novelty.
* Strong Software Engineer: You design modular, testable, and extensible systems and apply software engineering best practices consistently.
* Production-Oriented Thinker: You consider latency, memory, hardware constraints, observability, and lifecycle management from day one.
* Data-Driven Evaluator & Pragmatist: You treat data as a first-class component of the system, design robust evaluation datasets, and rigorously benchmark alternatives to select solutions based on measurable trade-offs.
* System-Level Collaborator: You think beyond the model and understand how ML components interact with robotics, control logic, and distributed AV systems.
Responsibilities
* Evaluate and benchmark state-of-the-art ML models and algorithms for perception, tracking, and multimodal awareness.
* Design and maintain reproducible evaluation pipelines measuring model performance, latency, memory footprint, and robustness.
* Integrate ML models into production systems in collaboration with Robotics and Platform teams.
* Optimize inference pipelines for real-time performance on constrained hardware (CPU/GPU/edge devices, Q-SYS Cores).
* Improve model efficiency using quantization, pruning, distillation, and runtime optimization techniques.
* Write production-grade Python (and C++ where appropriate) following clean architecture and modular design principles.
* Contribute to CI/CD pipelines, automated testing, regression validation, and performance monitoring for ML components.
* Ensure reproducibility, versioning, and traceability of models, datasets, and experiments.
* Collaborate to industrialize promising prototypes into scalable production systems.
* Work with Product and System Architects to align ML solutions with hardware and product roadmap constraints.
Qualifications
* MSc or PhD in Computer Science, Engineering, Robotics, or related technical field.
* 5+ years of hands-on experience in machine learning engineering or applied ML roles.
* Proven experience integrating ML models into production systems.
* Strong proficiency in Python and modern ML frameworks ( PyTorch, TensorFlow, ONNX).
* Solid software engineering fundamentals, including modular design, code reviews, testing strategies, and CI/CD.
* Experience optimizing models for real-time or resource-constrained environments.
* Understanding of system-level trade-offs in latency-sensitive or distributed architectures.
* Ability to work independently and drive technical decisions within architectural guidelines.
* Strong communication skills and experience collaborating in cross-functional engineering teams.
* Preferred experience with one or more of the following:
* Experience with computer vision, tracking, or multimodal perception systems.
* Experience with C++ in performance-critical environments.
* Familiarity with AV systems, media pipelines, or robotics-oriented architectures.
* Exposure to ROS, TensorRT, or MLOps tools (MLflow, Weights & Biases, Docker).
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