COMPANY DESCRIPTION

Fortune Brands Innovations, Inc. is an industry-leading innovation company focused on creating smarter, safer and more beautiful homes and improving lives. Our driving purpose is that we elevate every life by transforming spaces into havens. We believe our work and our brands can have incredibly positive impacts for not just our business and shareholders, but for people and the planet, too. When you join Fortune Brands, you become part of a high-performing team who are empowered to think big, learn fast and make bold decisions. We support an inclusive and diverse culture where everyone is encouraged and empowered to be their authentic selves, and where our differences and unique perspectives are a key strength.

JOB DESCRIPTION

We are seeking a talented and innovative Machine Learning Engineer to join our team of AI/ML engineers. This role focuses on developing, maintaining, and enhancing machine learning models. The ideal candidate will have strong experience in computer vision, deep learning, and deploying ML models in containerized environments.
Position location –This position is eligible for a hybrid schedule (Tu-Wed-Thu – In Office) based in Deerfield, IL
We currently do not sponsor at this time.

BASIC QUALIFICATIONS:

• Master’s or Bachelor’s degree in Computer Science, Machine Learning, or related field.
• 3+ years of experience in developing and deploying machine learning models.
• Strong background in computer vision and image classification.
• Experience with Azure (a plus if you have Azure AI Solutions)
• Proficiency in Python and machine learning frameworks (TensorFlow required, ONNX or PyTorch a plus).
• Experience with containerized ML deployments (Docker, Kubernetes).
• Familiarity with REST APIs and microservices architectures.
• Knowledge of image processing techniques and computer vision algorithms.
• Understanding of ML model versioning, monitoring, and maintenance.

PREFERRED QUALIFICATIONS:

• Experience with image recognition or similar identification systems.
• Background in developing systems that incorporate human feedback for model improvement.
• Familiarity with SQL or similar databases for storing model outputs and metadata.
• Experience with CI/CD pipelines for ML model deployment.

• Develop and enhance TensorFlow-based image classification models.
• Design and implement training pipelines for model iteration and improvement.
• Analyze model performance and implement techniques to improve accuracy and reduce false positives.
• Maintain and optimize existing ML inference services deployed in Kubernetes.
• Collaborate with Engineers to ensure seamless integration between machine learning components and API services.
• Monitor model performance in production and implement strategies to handle data drift.
• Work with labeled datasets from the review interface to improve model quality.
• Develop data preprocessing pipelines for image normalization and augmentation.
• Implement feedback loops utilizing corrections from subject matter experts and metrics.
• Research state-of-the-art computer vision techniques applicable to image recognition.
• Evaluate new approaches for improving identification accuracy and processing efficiency.
• Prototype and implement new features leveraging machine learning capabilities.
• Work with full-stack engineers to integrate ML components into the broader application.
• Work within Azure for the entire process - we build a lot of our product within Azure
• Document ML approaches, model versions, and performance metrics.