Staff Backend Software Engineer

GoDaddy; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

GoDaddy is seeking a Staff Software Engineer to lead the design and evolution of infrastructure and services that enable production ML workloads at scale. You will work with ML Scientists, Data Engineers, and Product teams to deliver robust, observable platforms and drive architectural excellence across a global team.

The role requires deep expertise in Python/Go/TypeScript, distributed systems, containers, and AWS, with a proven track record mentoring engineers and delivering high-availability

Qualifications

• 7+ years of software engineering experience building and operating large-scale distributed systems.
• Strong proficiency in Python, Go, and/or TypeScript with API design and architecture focus.
• Hands-on with containers, Kubernetes, and cloud-native AWS services.
• Experience leading complex technical initiatives and mentoring engineers.

Responsibilities

• Lead design and evolution of ML infrastructure, platforms, and services for production models.
• Collaborate with ML Scientists, Data Engineers, and Product teams to deliver scalable ML solutions.
• Influence architecture, drive engineering excellence, and mentor a distributed team.
• Develop observability, performance, and cost-optimization strategies for ML workloads.

Skills

Python

Go

TypeScript

API design

System architecture

Distributed systems

Kubernetes

Docker

AWS

Mentoring

Observability

AI workloads

CI/CD

Education

Bachelor’s degree in CS or related field

Tools

CDK

Terraform

CloudFormation

Prometheus

Grafana

OpenTelemetry

Job description

• At GoDaddy, we’re building the next generation of AI and machine learning capabilities that power experiences for millions of entrepreneurs worldwide. Our Machine Learning Engineering team bridges the gap between research and production, transforming cutting‑edge models into scalable, reliable, and observable services that operate at global scale
• We’re looking for a Staff Software Engineer to lead the design and evolution of the infrastructure, platforms, and services that enable machine learning models to run in production. This is a highly technical, hands‑on role where you’ll work closely with ML Scientists, Data Engineers, and Product teams to deliver robust ML-powered solutions while helping shape the future of our machine learning platform
• As a senior technical leader, you’ll influence architecture, drive engineering excellence, and mentor engineers across a globally distributed team

• 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