Metropolis is looking for a Staff Computer Vision Engineer to lead the design and development of perception algorithms and systems that power Metropolis’s “AI for the Real World”. We are developing a broad suite of computer vision systems that span both edge and cloud environments, and enable checkout-free experiences in a variety of applications.  As a senior technical leader, you will drive the optimization, integration, and validation of advanced perception models for real-time deployment on edge and cloud platforms. This will include solving complex challenges in object detection, tracking, and recognition, and may span video analytics and multi-modal systems. You will work closely with cross-functional teams throughout the entire perception system lifecycle, from development to rigorous testing, while driving innovations in computer vision and machine learning that directly enhance the accuracy, reliability, and performance of applications core to our company. 

Excellence in this position involves leading innovation in computer vision, delivering impactful results, and fostering growth through technical leadership and mentorship within the ML team..  You must be able to thrive in a entrepreneurial environment, working collaboratively in a fast-paced environment that often has multiple stakeholders.  You won’t be afraid to break new technological ground at Metropolis, and are more than willing to roll up your sleeves, dig in, and get the job done.  If you have a background in computer vision and perception, and are excited by developing systems that go into the real world to solve real problems, please reach out!

• Architect and develop advanced perception algorithms for tasks such as object detection, tracking, semantic segmentation, and scene understanding.

• Take initiative to identify gaps, bottlenecks, and opportunities in perception performance and system design—then drive solutions from concept through deployment.

• Define and implement key metrics and KPIs to rigorously evaluate perception system accuracy, robustness, and scalability across diverse real-world conditions.

• Drive system-level debugging and root cause analysis for perception failures in production environments.

• Collaborate with hardware, ML, and software engineering teams to improve data pipelines, model deployment frameworks, and sensor configurations.

• Mentor and lead by example, promoting best practices in scalable architecture, model evaluation, and engineering excellence within the computer vision team.

• Research, prototype, and integrate new machine learning or deep learning approaches applicable to perception problems.

• Participate in cross-team initiatives to improve system reliability, labeling quality, simulation-based validation, optimizing perception models and production-readiness of perception models.

• Stay ahead of the curve by researching, prototyping, and integrating emerging deep learning techniques and tools into our perception stack.

• M.S. or Ph.D. in Computer Science, Electrical Engineering, Robotics, or related field with a focus on computer vision or machine learning.
• 8+ years of industry experience in developing and deploying perception algorithms in real-world applications.
• Strong proficiency in modern deep learning frameworks (e.g., PyTorch, TensorFlow, Qualcomm Chip) and classical CV libraries (e.g., OpenCV).
• Deep expertise in one or more of: object detection, multi-object tracking, segmentation, depth estimation, or sensor fusion.
• Solid experience with deployment of ML models on edge devices and Cloud Platform (e.g., GPU/embedded).
• Excellent programming skills in Python or C++.
• Strong understanding of 2D/3D geometry and image processing.
• Experience working with large-scale datasets, including data curation, annotation,  evaluation, Airflow pipeline and messaging platforms (e.g. MQTT, Kafka, or ROS2)
• Familiarity with cloud platforms (AWS, GCP, or Azure), containerization (Docker), and orchestration (ECS, Kubernetes)
• Familiarity with ML model training, Data Annotation and Model Evaluation
• Strong understanding of the agile development process and CI/CD pipelines and tools (e.g., Github Actions, Jenkins). 
• Proven track record of technical leadership and mentorship in high-performing engineering teams.
• Publications or patents in computer vision or applied machine learning.