Architect, design, and lead the implementation of scalable, secure, and resilient infrastructure for AI/ML workloads
Full stack engineer to design and develop scalable SaaS application and services
Build and maintain the continuous integration and continuous deployment (CI/CD) pipelines specifically for AI models
Act as a subject matter expert and mentor for junior engineers
Ensure the reliability, security, and performance of AI systems
Stay ahead of industry trends and bring innovative AI solutions to the table

Requirements

8+ years of experience in DevOps, ML Infrastructure, or Platform Engineering
Deep, expert-level knowledge of at least one major cloud provider (e.g., AWS, Azure, or GCP)
Hands-on experience with ML orchestration and platform tools like Kubeflow, MLflow, or Amazon SageMaker
Deep expertise with Docker and Kubernetes
Strong coding skills in languages such as Python, Go, or Bash
Demonstrable experience in using AI development tooling (Claude, Cursor, CoPilot)
Proficiency with tools like Terraform or Ansible
Experience building robust and automated CI/CD pipelines using tools like GitHub Actions, GitLab CI/CD, or Jenkins
Excellent collaboration and communication skills

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

DevOpsML InfrastructurePlatform EngineeringCloud ComputingML orchestrationDockerKubernetesPythonGoBash

Soft Skills

collaborationcommunicationmentoring