Principal Computer Vision AI Engineer

Ecolab - Saint Paul, MN

Full-time - Mid Level

Saint Paul, MN

10,001+ employees

Chemical Manufacturing

About the position

Ecolab is seeking an experienced Computer Vision AI Engineer to join a dynamic team that is at the forefront of technological innovation. This role is pivotal in leveraging cutting-edge AI technologies to create novel solutions that optimize operations for clients, particularly within the restaurant industry. The work being done is transformative, aiming to enhance the efficiency and sustainability of restaurant operations. As a key player in this new division, you will have the unique opportunity to shape its culture and direction, impacting the success of innovative projects and helping to define the future of product offerings. In this collaborative environment, you will experience the best of both worlds: the agility and creativity of a startup combined with the stability and resources of a global leader. The team fosters innovation while providing the support and security necessary for you to thrive. Your responsibilities will include aiding in the creation of product roadmaps by informing key technical decisions and best practices for Vision AI use. You will develop and implement computer vision algorithms using libraries such as OpenCV and frameworks for Convolutional Neural Networks (CNNs) for tasks like object detection, tracking, and image classification. Additionally, you will oversee the MLOps lifecycle, which includes data collection, labeling, model training, evaluation, inference, refinement, and monitoring. Collaboration with cross-functional teams will be essential to integrate vision systems with hardware and software platforms, ensuring high performance and reliability. You will also conduct research on state-of-the-art recognition techniques and stay current with industry trends, ensuring that Ecolab remains a leader in the field of computer vision and AI.

Responsibilities

• Aid in creating product roadmap by informing key technical decisions and best practices for Vision AI use
• Develop and implement computer vision algorithms using libraries such as OpenCV and frameworks for CNNs for object detection, tracking, and image classification
• Oversee the MLOps lifecycle including data collection, labeling, model training, evaluation, inference, refinement, and monitoring
• Collaborate with cross-functional teams to integrate vision systems with hardware and software platforms, ensuring high performance and reliability
• Conduct research on state-of-the-art recognition techniques and stay current with industry trends

Requirements

• 10 years of work experience with a specialization in computer vision or machine learning Vision AI
• Proficiency in Python programming
• Strong knowledge of core computer vision algorithms and libraries like OpenCV
• Experience with convolutional neural networks for computer vision tasks
• Solid understanding of supervised and unsupervised machine learning algorithms
• Expertise in MLOps, covering the full model lifecycle
• Proven experience in collecting, cleaning, and organizing large datasets for training and testing models
• Demonstrated ability to implement and fine-tune computer vision models for various item classes

Nice-to-haves

• Advanced degree (MS/PhD) in Computer Science, Electrical Engineering, Applied Mathematics
• Experience with advanced object detection frameworks like YOLO and Roboflow
• Experience using PyTorch, AutoML and similar model training frameworks
• Familiarity with Azure Machine Learning and Azure Vision AI
• Experience with containerization tools like Docker and orchestration with Kubernetes
• Proven experience deploying distributed Cloud & Edge solutions
• Knowledge of multi-modal language models like GPT-4V and specialized language models like the Phi family
• Interest in collaborating with partners outside of core team / organization
• Openness to experimental approaches typical of tech start-ups

Benefits

• Comprehensive and market-competitive benefits to meet the needs of associates and their families