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This listing was closed on Jul 18, 2026.
Browse Open JobsMLOps Engineer
Summary by AIEngineer.careers
MLOps Engineer is a MLOps Engineer role (full-time). with Scale.jobs. in REMOTE, WORLDWIDE. Imported listing (source: linkedin.com). Apply on the employer's site (linkedin.com).
Imported listing (source: linkedin.com) · Apply on linkedin.com
REMOTE · WORLDWIDE
—
Full-time
MID
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from linkedin.com
The role bridges ML research and production-grade systems, owning infrastructure, pipelines, and CI/CD for deploying and scaling ML models.
Responsibilities
- Design, build, and maintain robust ML pipelines using Kubeflow, Airflow, or Prefect for automated model retraining and batch inference
- Develop and manage feature stores (e.g., Feast or Tecton) for consistent feature engineering
- Deploy ML models as high-throughput, low-latency microservices using Triton Inference Server, KServe, or FastAPI
- Implement monitoring and alerting for model drift and system performance using Prometheus, Grafana, and Evidently AI
- Containerize ML workloads with Docker and orchestrate on Kubernetes
- Establish CI/CD pipelines for automated testing and deployment (GitOps, GitHub Actions, GitLab CI)
Requirements
- 3-6 years of experience in DevOps, MLOps, or Software Engineering with focus on ML infrastructure
- Proficiency in Python and familiarity with shell scripting, Terraform, and cloud platforms (AWS, GCP, or Azure)
- Hands-on experience with Kubernetes and containerized applications at scale
Scale.jobs
San Francisco · US · 86+ employees
Scale.jobs is a human-powered job application service that provides virtual assistants to apply to jobs on behalf of job seekers. The company offers custom resume and cover letter creation to help candidates save time and accelerate their search in the US job market.
