Machine Learning Engineer Senior

We use technology to solve problems in spaces, light, and more things to come… for our customers, our communities, and our planet.

Acuity Inc. (NYSE: AYI) is a market-leading industrial technology company. We use technology to solve problems in spaces, light, and more things to come. Through our two business segments, Acuity Brands Lighting and Lighting Controls (ABL) and the Intelligent Spaces Group (ISG), we design, manufacture, and bring to market products and services that make a valuable difference in people’s lives.

We are positioned at the intersection of sustainability and technology. Our businesses develop technology that helps save our customers energy and reduce their carbon emissions. We achieve growth through the development of innovative new products and services, including lighting, lighting controls, building management solutions, and location-aware applications.

Job Summary

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).

Key Tasks & Responsibilities (Essential Functions)

• 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.

Skills and Minimum Experience Required

• 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 Skills and Experience

• 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).

Other

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.

We value diversity and are an equal opportunity employer. All qualified applicants will be considered for employment without regards to race, color, age, gender, sexual orientation, gender identity and expression, ethnicity or national origin, disability, pregnancy, religion, covered veteran status, protected genetic information, or any other characteristic protected by law.

Accommodation for Applicants with Disabilities: As an equal opportunity employer, Acuity Inc. is committed to providing reasonable accommodations in its application process for qualified individuals with disabilities and disabled veterans. If you have difficulty using our online system due to a disability and need an accommodation, you may contact us at (770) 922-9000, select option 4. Please clearly indicate what type of accommodation you are requesting and for what requisition.

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