About the job
ABOUT TALON. ONE:
Talon. One is a cutting-edge incentives engine that seamlessly integrates loyalty, promotions, and gamification into a single, powerful platform. With enterprise-grade security and scalability, Talon. One enables organizations to craft personalized, profitable promotions and loyalty programs using any data they choose.
Currently, over 250 of the world’s most beloved brands, including Adidas, Sephora, and Carlsberg, leverage Talon. One to foster deeper engagement and cultivate lasting loyalty among their customers.
ABOUT THE TEAM:
We are a dedicated cross-functional team comprising engineers, data scientists, product managers, and an engineering manager, all focused on data solutions. You will play a pivotal role within our expanding Intelligence Tribe, where we are enthusiastic about exploring new tools and technologies. Our culture thrives on collaborative brainstorming to tackle challenges and implement best practices.
ABOUT THE ROLE:
We are on the lookout for a Senior MLOps Engineer to become a vital member of our dynamic Intelligence Platform team. In this position, you will design, develop, and maintain a robust MLOps infrastructure and workflows that facilitate the deployment, monitoring, and scalability of our machine learning models. Collaboration with data scientists, engineers, and the Infrastructure team will be key as we work to optimize the machine learning lifecycle and introduce innovative solutions into production.
ONCE YOU ARE HERE, YOU WILL:
- Develop and sustain MLOps pipelines that automate data preparation, model training, evaluation, deployment, and monitoring of ML models and data pipelines.
- Design scalable infrastructure using our cloud platform and technologies such as Kubernetes, Docker, and Terraform.
- Implement CI/CD processes for ML models, ensuring reproducibility, reliability, and version control.
- Monitor model performance and data drift in production, instituting automated retraining workflows as necessary.
- Collaborate with data scientists and engineers to operationalize machine learning models in a secure, efficient, and scalable manner.
- Oversee model registries, metadata tracking, and experiment management tools.
- Promote and assist in the implementation of MLOps best practices organization-wide.
- Ensure adherence to security, governance, and ethical AI standards.
WHAT WE EXPECT YOU TO BRING TO THE TABLE:
- 6+ years of experience in MLOps or related fields.
