[Hiring] Senior Software Engineer @GoDaddy

Role Description

The ML Engineering (MLE) team builds and operates the production infrastructure that brings ML models to life across GoDaddy's global markets. We own model serving infrastructure, CI/CD pipelines for model deployment, the Model Gateway, API design, observability, and all inference context infrastructure. We partner with ML scientists who build the models — our job is to design the systems and make those models reliable, scalable, and observable in production.

We are looking for a Senior Software Development Engineer to join our India-based engineering team. This is a mid-level IC role focused on building and operating ML infrastructure — writing production code, building deployment pipelines, improving observability, and partnering with ML scientists to productionize models! You'll work closely with the India-based engineering manager and collaborate daily with engineers in North America and India.

What you'll get to do:

• Build and maintain model serving infrastructure — deploying ML models to production endpoints, managing autoscaling, and ensuring low-latency inference.
• Develop and improve CI/CD pipelines for model training, testing, deployment, and promotion across environments.
• Write production services in Python and Go, with infrastructure-as-code in TypeScript (CDK). Partner with ML scientists to translate trained models into production-grade, monitored, and maintainable services.
• Build and maintain online feature stores, inference context APIs, and data pipelines that feed production models.
• Instrument services for observability — metrics, logging, tracing, alerting — and participate in on-call rotation. Contribute to the Model Gateway for experimentation, traffic routing, and fallback logic.
• Debug production issues, investigate performance regressions, and drive root-cause analysis. Collaborate daily with engineers, scientists, data engineers, and product teams across time zones.

Qualifications

• 3–5 years of software development experience shipping production applications.
• Proficiency in Python; working knowledge of Go or TypeScript is a plus.
• Experience with AWS services (ECS/EKS, Lambda, DynamoDB, S3, or equivalents).
• Solid understanding of microservices, REST APIs, and distributed systems fundamentals.
• Experience building or maintaining CI/CD pipelines (GitHub Actions, Jenkins, or similar).
• Experience with containerization (Docker) and orchestration basics (Kubernetes or ECS).
• Strong communication skills — ability to collaborate across time zones with engineers and scientists.
• Ownership mindset — willingness to take end-to-end responsibility for features from design through production.

Requirements

• Experience with ML model serving frameworks (SageMaker, vLLM, TorchServe, Triton).
• Familiarity with observability tools (OpenTelemetry, Prometheus, Grafana, CloudWatch).
• Experience with infrastructure as code (CDK, CloudFormation, Terraform).
• Exposure to ML concepts — model training, inference, feature engineering, drift detection.
• Experience with AI-assisted development tools.
• Bachelor's or Master's degree in Computer Science, Engineering, or equivalent experience.

Benefits

• Paid time off.
• Retirement savings (e.g., 401k, pension schemes).
• Bonus/incentive eligibility.
• Equity grants.
• Participation in our employee stock purchase plan.
• Competitive health benefits.
• Other family-friendly benefits including parental leave.