Senior Infrastructure Engineer, AI/ML Systems
- Build and operate deployment pipelines for AI services, covering CI/CD, 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 take prototypes into production, including system design for net-new services
- Own production reliability for AI services: monitoring, alerting, debugging, performance, and cost
- Spot repeated patterns and turn them into reusable templates, so the team can ship its second and third variant of something without rebuilding it
- Six or more years in infrastructure, DevOps, platform, or ML engineering, with ownership of systems running in production
- Deep hands-on experience across a wide range of AWS services, including compute, networking, storage, deployment, and monitoring
- Infrastructure-as-code experience (Terraform, CDK, or CloudFormation)
- Experience with containers and modern deployment patterns (Docker required, Kubernetes or ECS/EKS a plus), applied to CI/CD pipelines designed and operated for production services
- Experience with orchestration and workflow tooling (Airflow, Dagster, Argo, Step Functions, or similar)
- Comfort working through ambiguity and collaborating directly with data scientists and researchers
- Experience with ML platform components and data pipeline orchestration at scale
- Experience running LLM-based or retrieval-based systems in production
- Experience operating specialized data stores, including graph databases
- Experience building internal tooling, templates, or reference implementations that other engineers adopted
- HUF 1.5M – HUF 2.2M per month compensation
- Competitive compensation, plus participation in ownership program
- Flexible work culture with remote, hybrid and in-office collaboration spaces
- Generous time off, including local holidays and annual “Dim the Lights” period in late December
- Comprehensive wellness programs and mental health support
- Learning and development resources, including professional development tools and tuition reimbursement
- Technology and tools needed to do best work
- Motivosity employee recognition program
- A culture rooted in inclusivity, support, and meaningful connection