Staff MLOps Engineer
Inworld AI
full-time
Posted on:
Location Type: Hybrid
Location: Mountain View • California • 🇺🇸 United States
Visit company websiteSalary
💰 $180,000 - $280,000 per year
Job Level
Lead
Tech Stack
AnsibleAzureC++CloudGoGoogle Cloud PlatformKubernetesOpen SourceOraclePythonTerraform
About the role
- 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.
Requirements
- 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
- 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).
- 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.
Benefits
- equity
- benefits 📊 Resume Score Upload your resume to see if it passes auto-rejection tools used by recruiters Check Resume Score
Applicant Tracking System Keywords
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Hard skills
MLOpsCI/CDKubernetesTerraformArgoCDGitHub ActionsGolangPythonBashSLURM
Soft skills
technical leadershipmentoringcollaborationproblem-solvingadaptabilitycommunicationefficiency enhancementprocess improvementownershipexperimental mindset