About BeGig
BeGig is the leading tech freelancing marketplace. We empower innovative, early-stage, non-tech founders to bring their visions to life by connecting them with top-tier freelance talent. By joining BeGig, you’re not just taking on one role—you’re signing up for a platform that will continuously match you with high-impact opportunities tailored to your expertise.
Your Opportunity
AI DevOps Engineer
Engage with startups and scaleups on a flexible, remote-first basis—hourly or project-based.
Role Overview
As an AI DevOps Engineer, you will:
Automate ML Workflows
: Build CI/CD pipelines tailored for AI/ML projects including model training, validation, deployment, and rollback.Deploy AI Infrastructure
: Manage containerized AI services (LLMs, inference endpoints, pipelines) on Kubernetes or other orchestration platforms.Optimize Compute Resources
: Design cost-efficient GPU/CPU allocation strategies and autoscaling policies across cloud infrastructure.Monitor AI Systems
: Implement logging and monitoring for AI workloads using Prometheus, Grafana, ELK, or similar stacks.Model Ops & Versioning
: Enable robust model tracking, registry management, and reproducible pipelines using tools like MLflow, DVC, or SageMaker.Secure and Scale
: Apply best practices in access control, environment isolation, and infrastructure scaling for multi-tenant AI products.
Technical Requirements & Skills
Experience
: Minimum 2+ years in DevOps or MLOps with direct exposure to AI/ML systems.CI/CD
: Hands-on experience with GitHub Actions, GitLab CI, Jenkins, or similar tools to automate AI model and app deployment.Cloud & Containers
: Proficient in AWS, GCP, or Azure with containerization (Docker) and orchestration (Kubernetes).Monitoring
: Familiarity with Prometheus, Grafana, ELK, or similar monitoring/logging solutions.MLOps Tools
: Experience with MLflow, Weights & Biases, DVC, or SageMaker for model lifecycle management.Scripting & Automation
: Strong scripting skills in Python, Bash, or Go for infrastructure automation and custom tooling.
What We’re Looking For
- A systems and automation expert who understands the specific needs of AI-driven environments.
- A freelancer who thrives on performance, reproducibility, and operational resilience.
- A DevOps mindset builder who brings structure to the often chaotic world of experimental AI development.
Why Join Us?
Immediate Impact
: Help early-stage and growth-stage startups deploy, monitor, and scale their AI systems effectively.Remote & Flexible
: Choose your working model—hourly or project-based—from anywhere.Future Opportunities
: Be continuously matched with MLOps, AI tooling, and infrastructure engineering roles.
Growth & Recognition
