AI DevOps Engineer
BeGig
Job Overview
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Job Description
AI DevOps Engineer at BeGig
About BeGig
BeGig is a tech freelancing platform that connects skilled technology professionals with companies and founders seeking specialized expertise on a flexible, project-based basis.
Your Opportunity
As an AI DevOps Engineer on BeGig, you’ll work on freelance projects focused on building, deploying, and maintaining scalable infrastructure for AI and machine learning systems. You’ll enable teams to reliably move AI models from development to production—without the constraints of a traditional full-time role.
What You’ll Do
- Design and maintain CI/CD pipelines for AI and ML workflows
- Deploy, scale, and monitor AI/ML services and model inference systems
- Manage cloud and containerized infrastructure for AI workloads
- Implement MLOps practices for model versioning, monitoring, and rollback
- Optimize system performance, cost, and resource utilization
- Build observability, logging, and alerting for AI services
- Automate infrastructure provisioning using IaC tools
- Ensure security, reliability, and compliance of AI systems
- Collaborate with AI/ML engineers and backend teams to support production AI deployments
What We’re Looking For
- Strong hands-on experience in DevOps, Cloud, or Platform Engineering
- Experience supporting AI/ML or data-intensive systems in production
- Proficiency with cloud platforms (AWS, GCP, Azure)
- Experience with Docker, Kubernetes, and container orchestration
- Familiarity with MLOps tools and workflows (MLflow, Kubeflow, Airflow, etc.)
- Strong scripting skills (Python, Bash)
- Experience with CI/CD tools and Infrastructure as Code (Terraform, CloudFormation)
- Knowledge of monitoring and logging stacks
- A self-driven freelancer who can independently own AI infrastructure and operations
Why BeGig
- Flexible freelance opportunities aligned with your AI DevOps expertise
- Work with multiple clients building and scaling real-world AI systems
- Get matched with relevant, high-quality engagements through the BeGig platform
- Be part of a trusted network of AI, DevOps, and platform professionals
Apply now to join BeGig as an AI DevOps Engineer and help teams scale AI reliably in production.
Key skills/competency
- DevOps
- Machine Learning Operations (MLOps)
- Cloud Computing (AWS, GCP, Azure)
- Containerization (Docker, Kubernetes)
- CI/CD
- Infrastructure as Code (IaC)
- Python Scripting
- System Monitoring
- AI/ML Infrastructure
- Scalability
How to Get Hired at BeGig
- Research BeGig's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor to understand their freelancing platform model.
- Customize your resume for AI DevOps: Highlight strong experience in DevOps, Cloud, MLOps, and specific tools like Docker, Kubernetes, AWS, GCP, Azure, and Terraform.
- Showcase your AI/ML project portfolio: Prepare examples of production AI/ML infrastructure deployments, CI/CD pipelines, and scalability solutions you've implemented.
- Prepare for technical assessments: Expect questions on cloud architecture, container orchestration, scripting (Python/Bash), and MLOps best practices relevant to AI systems.
- Demonstrate freelance readiness: Emphasize your ability to work independently, manage projects, and collaborate remotely as a self-driven AI DevOps Engineer.
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