Senior Infrastructure Engineer, AI/ML Systems
Instructure, Inc.3 hours ago
Responsibilities
- Build and operate deployment pipelines for AI services using infrastructure-as-code, environment promotion, and rollback.
- Deploy and operate model serving, batch scoring, and orchestration pipelines across development, staging, and production.
- Partner with data scientists and applied AI engineers to productionize prototypes and design net-new services.
- Own production reliability for AI services, including monitoring, alerting, debugging, performance, and cost.
- Create reusable templates and patterns that help engineers ship subsequent service variants efficiently.
Requirements
- Six or more years of experience in infrastructure, DevOps, platform, or ML engineering with ownership of production systems.
- Deep hands-on experience with a broad range of AWS services across compute, networking, storage, deployment, and monitoring.
- Experience with infrastructure-as-code using Terraform, CDK, or CloudFormation.
- Required experience with Docker and modern deployment patterns; Kubernetes or ECS/EKS experience is a plus.
- Experience designing and operating production CI/CD pipelines.
- Experience with orchestration and workflow tools such as Airflow, Dagster, Argo, or Step Functions.
- Ability to work through ambiguity and collaborate directly with data scientists and researchers.
- Bonus: experience with ML platform components, data pipeline orchestration at scale, LLM-based or retrieval-based systems, specialized data stores including graph databases, or internal tooling and reference implementations.
Benefits
- Onsite collaboration is required Tuesday and Wednesday, with Thursday strongly encouraged.
- Competitive compensation and participation in an ownership program for full-time employees.
- Flexible remote, hybrid, and in-office work arrangements vary by role, team, and location.
- Generous time off, local holidays, and an annual late-December “Dim the Lights” period based on departmental needs.
- Wellness programs and mental health support.
- Learning and development resources, professional development tools, and tuition reimbursement.
- Company-provided technology and tools, employee recognition through Motivosity, and an inclusive, collaborative culture.
Tech Stack
Categories
About Instructure, Inc.
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