Software Engineer - ML

Salary Range $123,000 - $160,000*

Job Description:

WHO WE ARE:

Saks Global is the largest multi-brand luxury retailer in the world, comprising Saks Fifth Avenue, Neiman Marcus, Bergdorf Goodman, Saks OFF 5TH, Last Call and Horchow. Its retail portfolio includes 70 full-line luxury locations, additional off-price locations and five distinct e-commerce experiences. With talented colleagues focused on delivering on our strategic vision, The Art of You, Saks Global is redefining luxury shopping by offering each customer a personalized experience that is unmistakably their own. By leveraging the most comprehensive luxury customer data platform in North America, cutting-edge technology, and strong partnerships with the world's most esteemed brands, Saks Global is shaping the future of luxury retail.

Saks Global Properties & Investments includes Saks Fifth Avenue and Neiman Marcus flagship properties and represents nearly 13 million square feet of prime U.S. real estate holdings and investments in luxury markets. 

YOU WILL BE:

The ML Engineer I will join the innovative Machine Learning (ML) team at Saks Fifth Avenue, contributing directly to the development and deployment of advanced machine learning systems and services. In this highly technical role, you will write performant, scalable, and reliable software solutions in Kotlin, Rust, and GraphQL, operating primarily within Kubernetes environments. You will actively participate in the full development lifecycle, from design and implementation through testing and deployment, collaborating closely with senior engineers, data scientists, and product teams to build solutions that power personalization, recommendation systems, customer insights, and predictive analytics for Saks Fifth Avenue.

WHAT YOU WILL DO:

• Develop and optimize backend services in Kotlin and Rust, applying systems programming techniques, concurrency control, and performance tuning to support real-time ML-powered features at scale

• Design, implement, and maintain GraphQL APIs, including schema definition, query/mutation development, and integration with ML systems to enable seamless data access and interaction for client applications

• Deploy and manage containerized applications in Kubernetes, using Infrastructure as Code (IaC) tools to automate provisioning, scaling, and monitoring of ML services in cloud-native environments

• Collaborate with data scientists to productionize machine learning models, ensuring robust integration, reliable serving, and efficient inference pipelines within Saks Fifth Avenue’s technology stack

• Apply software engineering best practices—including use of data structures, algorithms, and architectural patterns—to design, debug, and deliver maintainable, high-quality code for complex ML-driven applications

WHAT YOU WILL BRING:

• Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline.

• Proficiency in Kotlin and/or Rust, with strong foundational knowledge of systems programming, concurrency, and performance optimization.

• Familiarity and experience with GraphQL APIs, including schema design, queries, and mutations.

• Experience or academic exposure to containerized application development and orchestration using Kubernetes using Infrastructure as Code (IaC).

• Solid understanding of software engineering principles, including data structures, algorithms, and software architecture design patterns.

• Capability to effectively troubleshoot and debug complex software applications.

• Demonstrated interest or experience in machine learning systems, including deployment, serving, or integration of ML models.
   

Preferred Qualifications:

• Experience developing scalable, production-quality microservices or backend applications.

• Hands-on experience with continuous integration and continuous deployment (CI/CD) tools and processes.

• Knowledge of cloud-based environments, particularly Google Cloud Platform or AWS.

• Experience or exposure to additional programming languages relevant to ML such as Python, Scala, or Java.

• Familiarity with modern ML frameworks and tools, such as TensorFlow, PyTorch, or MLflow.

• Strong analytical thinking and problem-solving skills, combined with the ability to effectively communicate