Salary Range $123,000 - $160,000* Job Description:

Role Summary

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.

Role Description

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 Required Qualifications: 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 complex technical concepts clearly to team members. Ability to thrive in agile, fast-paced environments and collaborate effectively with interdisciplinary teams.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Saks.com is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

*The above expected salary range may have some variability based upon factors including, but not limited to, a candidate's overall experience, qualifications, and geographic location. If you are interested in the role, we encourage you to apply and, if selected to move forward in the interview process, you will have a chance to speak with our recruitment team regarding your specific salary expectations.