As the Senior ML Research Engineer on the intelligent AV team, you will lead the adoption of cutting-edge machine learning models and algorithms, enhancing the awareness and perception engine behind Q-SYS VisionSuite. In close collaboration with our ML Architect, you will bridge the gap between state-of-the-art research and production systems. You will work alongside talented Software, Robotics, and Machine Learning Engineers to advance the next generation of intelligent audio-video systems for meeting spaces and smart buildings. Your key focus will be on driving innovation, expanding intelligent system capabilities, and shaping our data strategy, including collection and dataset curation, ensuring alignment with organizational goals. 

​Your Mindset 

​Innovative Thinker: Passionate about staying at the forefront of machine learning advancements and applying them to real-world challenges. 

​Scientist & Engineer: Driven to bridge the gap between research and practical applications, bringing the latest machine learning solutions into production. 

​Mentor and Advocate: Actively grow team members’ expertise and excitement about new advances. 

This hybrid position is based in Zurich or Athens.

Drive Innovation: Identify, experiment with, and implement cutting-edge ML algorithms, focusing on situational and perceptual awareness using ML techniques such as computer vision, sensor fusion and multimodal AI 

Collaboration & Research Partnerships: Build partnerships with universities at the master’s or PhD level to keep up with state-of-the-art advances. 

​​Integration into Production: Lead the integration of research innovations into production, in collaboration with the ML Architect. 

​Software Development: Contribute to and collaborate in our codebase following software development best practices. 

​​Strategic Leadership: Inform the ML vision and roadmap, identifying high-impact trends, and develop and align data strategies to support experimentation, training, and evaluation.​ 

​​Mentorship & Team Growth: Mentor team members, fostering a culture of innovation. 

​Hiring & Team Growth: Support recruitment efforts to expand the ML team. 

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Qualifications

• PhD in Engineering, Computer Science, or related fields, with a focus on machine learning, robotics, or similar.
• Minimum 3 years of hands-on experience deploying ML research in production environments within a collaborative and cross-disciplinary setting.
• At least 1 year of experience leading teams or projects, with strong collaboration and mentorship skills.
• Proficiency in Python, PyTorch, TensorFlow, or relevant ML frameworks.
• Software engineering skills, with experience in Git, code reviews, CI/CD and design patterns.
• Experience managing model lifecycles and data pipelines and ensuring real-time performance under constraints.
• Academic research collaboration experience, supervising academic research and contributing to successful technology transfers.

Plus

• Experience in developing models and algorithms for perception and situational awareness.
• Familiarity with MLOps tools like Weights and Biases, MLflow, and experience with Docker.
• Experience with ROS and C++.