Junior MLOps Engineer – Python, Kubernetes, Docker

A future-focused AI team needs a driven Junior MLOps Engineer to keep production models healthy and lightning-fast. You’ll weave together Python automation, Kubernetes orchestration, and observability practices to deliver resilient machine learning services at scale.

About the Role

– Partner with data scientists to transform research notebooks into production-ready containers.  

– Automate CI/CD pipelines that test, containerize, and release models across staging and prod clusters.  

– Instrument robust monitoring—latency, drift, resource use—and surface metrics through Grafana or Prometheus.  

– Debug failing jobs, flaky pods, or data bottlenecks to restore uptime quickly.  

– Document run-books, architecture diagrams, and standard operating procedures for repeatability.  

– Harden infrastructure with blue-green deployments, canary releases, and rollback strategies.  

– Continuously optimize workflow efficiency, cost, and carbon footprint.

Must-Have Skills

– Bachelor’s in Computer Science, Data Engineering, or related field.  

– 6+ months professional or academic experience as a Junior MLOps Engineer, DevOps, or similar.  

– Solid Python scripting for automation and tooling.  

– Working knowledge of Docker image creation and registry management.  

– Familiarity with Kubernetes objects (Deployments, Services, Helm charts).  

– Understanding of CI/CD concepts and Git workflows.  

– Comfort with Linux command line and shell scripting.  

– Clear, concise communication—verbal and written.

Nice-to-Have Extras

– Exposure to AWS, GCP, or Azure managed Kubernetes (EKS/GKE/AKS).  

– Hands-on with MLflow, Seldon Core, Kubeflow, or Vertex AI.  

– Experience configuring Grafana dashboards or Prometheus alerts.  

– Knowledge of Terraform or Pulumi for IaC.  

– Fundamentals of statistical model evaluation and drift detection.

Why You’ll Thrive

– Remote-friendly culture with flexible schedules across U.S. time zones.  

– Mentorship from senior MLOps architects who ship models to millions of users.  

– Opportunity to influence tooling and workflow choices—your voice matters from day one.  

– Continuous learning budget for certifications, conferences, and online courses.  

– Inclusive environment where innovation eclipses hierarchy.