Staff Backend Software Engineer

Join GoDaddy, a leading technology company that empowers entrepreneurs worldwide. As a Staff Backend Software Engineer, you will lead the design and evolution of the infrastructure, platforms, and services that enable machine learning models to run in production. You will work closely with ML Scientists, Data Engineers, and Product teams to deliver robust ML-powered solutions while shaping the future of our machine learning platform. This is a highly technical, hands-on role that requires strong proficiency in Python, Go, and/or TypeScript, as well as experience with containerization and orchestration technologies, cloud-native applications, and infrastructure on AWS.

• Concevoir et faire évoluer l'infrastructure, les plateformes et les services permettant aux modèles d'apprentissage automatique de fonctionner en production.
• Collaborer étroitement avec les scientifiques des données, les ingénieurs en données et les équipes produit pour livrer des solutions robustes alimentées par l'IA.
• Influencer l'architecture, promouvoir l'excellence en ingénierie et encadrer les ingénieurs au sein d'une équipe distribuée à l'échelle mondiale.

• Strong proficiency in Python, Go, and/or TypeScript, with deep expertise in API design, system architecture, scalability, resiliency, and performance optimization
• 7+ years of software engineering experience building and operating large-scale, production-grade distributed systems and microservices
• Experience with containerization and orchestration technologies including Docker, Kubernetes, ECS, or similar platforms supporting high-availability production workloads
• Hands-on experience building CI/CD pipelines, cloud-native applications, and infrastructure on AWS using services such as ECS, EKS, Lambda, DynamoDB, S3, IAM, and CloudWatch
• Proven ability to lead complex technical initiatives, influence architecture, collaborate across diverse stakeholders, and mentor engineers in a fast-paced environment
• We encourage you to apply even if your experience or skillset doesn’t align perfectly with every requirement
• Experience deploying and operating machine learning or generative AI workloads using technologies such as vLLM, Triton, TorchServe, SageMaker Endpoints, or similar serving frameworks
• Familiarity with modern observability practices and tools including OpenTelemetry, Prometheus, Grafana, and CloudWatch
• Experience with vector databases, feature stores, caching technologies (Valkey/Redis), and infrastructure-as-code solutions such as CDK, CloudFormation, or Terraform
• Knowledge of GPU infrastructure management, workload scheduling, performance tuning, and cloud cost optimization strategies
• Experience serving as a technical lead or mentor for distributed engineering teams and leveraging AI-assisted development tools to accelerate software delivery