Build the platform that turns machine learning experimentation into production-ready confidence. How do you help machine learning teams innovate faster without compromising trust? By building the platform that enables them to experiment, validate, and deploy models with confidence. As part of our Machine Learning Experimentation & Model Validation team, you'll design the tools and infrastructure that accelerate innovation while ensuring rigorous validation before production deployment. At the intersection of backend development, cloud infrastructure, and machine learning, you'll build services and tooling that make experimentation reproducible, validation reliable, and model deployment seamless. Working alongside an experienced team, you'll help bridge the gap between experimentation and production by delivering practical solutions that drive impact across Coveo. As one of our Senior Backend Software Developers, ML Platform, you will: Design, build, and evolve backend services and tooling that support the entire machine learning development lifecycle. Develop cloud-native infrastructure and automation using Python, Amazon Web Services (AWS), Terraform, and continuous integration and continuous delivery (CI/CD) practices. Partner directly with machine learning engineers and data scientists to understand their workflows, identify friction points, and deliver impactful improvements. Integrate and maintain modern machine learning tooling, including systems such as SageMaker Studio and MLflow, while continuously improving the platform's developer experience. Balance technical excellence with product thinking by making thoughtful trade-offs that maximize value for internal users. Contribute to a collaborative engineering culture by sharing knowledge, providing technical leadership, and driving continuous improvement across the team. Here is what will qualify you for the role: Professional experience building backend applications in Python, along with strong experience developing cloud-native solutions using Amazon Web Services (AWS). Experience building or maintaining machine learning platforms, MLOps tooling, or infrastructure that supports machine learning workflows. Strong understanding of infrastructure as code using Terraform and modern continuous integration and continuous delivery (CI/CD) practices. Demonstrated ability to work autonomously, communicate effectively with technical stakeholders, and influence decisions through collaboration and pragmatism. What will make you stand out: Experience integrating or supporting platforms such as SageMaker Studio or similar machine learning tooling. Familiarity with Java or experience working in polyglot engineering environments. Previous experience as a machine learning engineer or data scientist with a passion for building developer tooling. A strong product mindset with a genuine interest in improving user experience through thoughtful engineering decisions. Do you think you can bring this role to life? Send us your application, we want to hear from you! Join the Coveolife! We encourage all qualified candidates to apply regardless of, for example, age, gender, disability, gaps in CV, national or ethnic background. This job description was written by humans, assisted by AI. We may leverage technology in our hiring process to help us see the person behind the resume. Coveo is committed to providing accessible employment practices. If you require accommodation due to a disability at any point during the recruitment process, please contact HR@Coveo.com to discuss your needs.