Staff MLOps Engineer

• Build and scale MLOps systems to streamline the end-to-end ML model lifecycle on the Inworld AI platform, from training to deployment
• Design and implement robust model training, evaluation, and release pipelines
• Collaborate cross-functionally with ML and backend teams to design, deploy, and maintain scalable secure infrastructure for Inworld’s AI Engine and Studio
• Facilitate a "you build it, you run it" culture by providing the necessary tools and processes for monitoring the reliability, availability, and performance of services
• Manage CI/CD pipelines to ensure smooth and efficient code integration and deployment
• Identify and implement opportunities to enhance engineering speed and efficiency
• Provide technical leadership in ML engineering best practices, raise the technical bar, and mentor junior engineers in MLOps principles

• 7+ years of software engineering experience, with 5+ years of infrastructure-as-code
• Proficiency in managing Kubernetes clusters and applications, including creating Helm charts/Kustomize manifests for new applications
• Experience in creating and maintaining CI/CD pipelines for both applications and infrastructure deployments (using tools like Terraform/Terragrunt, ArgoCD, GitHub Actions, Ansible, etc.)
• Deep knowledge of at least one major cloud provider (Google Cloud Platform, Microsoft Azure, Oracle Cloud)
• Proficient in at least one backend programming/scripting languages such as Golang, Python, and Bash
• Knowledge of SLURM or similar job schedulers for distributed training
• Experience with data pipeline and workflow management tools
• Desire to work at a fast-growing Series A startup, comfortable with uncertainty, owning and scaling new products, and embracing an experimental and iterative development process
• In-office location: Mountain View, CA, United States. You must be available for hybrid work

• Familiarity with open source LLM and open source serving solution (e.g. vLLM or llama.cpp, kserve, etc) is a plus
• Experience with bare metal GPUs (optional)

equity and benefits