Title: MLOps / AI Ops Engineer
Job Type: Contract
Contract Length: 12 Months
Pay Range: $50/hr – $175/hr
Start Date: ASAP
Location: Remote
About The Opportunity
Our client, a leader in AI testing and Generative AI solutions, is looking for a skilled MLOps / AI Ops Engineer to join their team for a 12-month engagement. This project involves building and automating end-to-end CI/CD pipelines for machine learning models and establishing production observability frameworks to ensure model reliability and scalability. This is a high-impact role that requires a self-motivated professional who can hit the ground running and deliver results quickly.
Key Responsibilities & Deliverables
This role is focused on the successful completion of specific tasks and deliverables. Your responsibilities will include:
- Building and automating end-to-end CI/CD pipelines for machine learning models.
- Setting up observability and monitoring frameworks to track model accuracy, latency, and drift in real-time.
- Managing model deployment strategies (canary, A/B testing) to ensure zero-downtime updates.
- Automating the scaling of inference services based on incoming request volume.
- Establishing standard workflows for model governance and reproducibility.
Required Skills & Experience:
We are looking for someone with a proven track record of successful contract engagements. The ideal candidate will have:
- 4+ years of experience in MLOps or DevOps with an ML focus.
- Deep expertise in MLflow, Kubeflow, and CI/CD tools (GitHub Actions, Jenkins). This isn't a learning role—you need to be a subject matter expert.
- Demonstrated ability to work autonomously and manage your own time effectively to meet project goals.
- Experience with Python, Kubernetes, and cloud-native ML services.
- Strong communication skills to provide clear and concise status updates to the project team.