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Datology AIDatology AIRedwood City, CA

Software Engineer, Cloud Infrastructure

Designs, builds, and operates scalable multi-cloud infrastructure powering ML training, inference, and data curation pipelines. Collaborates with teams on AWS-focused systems using Kubernetes and IaC tools like Terraform.

180k – 300k/yr
HybridDevOps / SRE

About the role

What You'll Work On

  • Architect and maintain our multi-cloud infrastructure (primarily AWS, potentially Azure/GCP), with a focus on reliability, security, and scalability
  • Define and implement infrastructure-as-code best practices using Terraform, CloudFormation, Pulumi (and similar technologies)
  • Design and manage Kubernetes-based systems for model training, inference, and data processing workloads
  • Optimize our CI/CD pipelines and streamline deployment of services across environments
  • Build monitoring, alerting, and logging systems to ensure high system availability and observability
  • Collaborate with research and engineering teams to provide infrastructure support for training large-scale ML models
  • Ensure our infrastructure supports various deployment models (cloud, on-prem, hybrid) for enterprise use cases
  • Drive cost-efficiency strategies across compute and storage resources
  • Respond to and resolve infrastructure-related incidents with a sense of ownership and urgency

About You

  • You've led or helped build robust infrastructure systems at a startup or fast-moving engineering organization
  • Deep experience working with cloud providers (especially AWS), and ideally exposure to multi-cloud or hybrid-cloud setups
  • Strong with Kubernetes, Terraform, and containerized architectures
  • Confident with systems-level debugging—networking issues, memory leaks, resource bottlenecks, etc.
  • Comfortable writing clean, maintainable scripts in Bash, Python, or Go
  • You care deeply about building secure and scalable systems and take pride in reliable infrastructure
  • You're collaborative, humble, and ready to own high-impact projects end-to-end

Nice to Have

  • Experience supporting infrastructure for ML workloads (training pipelines, inference clusters, GPU orchestration)
  • Built or scaled infrastructure for teams working with large-scale datasets
  • Exposure to cost monitoring and optimization tools in cloud environments
  • Background supporting compliance and security in enterprise deployments

Compensation

Salary ranges from $180,000 to $300,000.

Comprehensive benefits: 100% covered health benefits, 401(k) with 4% match, unlimited PTO, wellness and learning stipends, daily lunches/snacks, relocation assistance.

Skills

AWSKubernetesTerraformCI/CDPythonGoBashCloudFormationPulumiGPU

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