Job Url: https://www.indeed.com/jobs?q=ai%2Fml&l=usa&sc=0kf%3Aattr%28DSQF7%29%3B&radius=25&from=searchOnDesktopSerp&start=20&vjk=30a8a2f6a3ed887b

Job Description: MLOps Engineer- job post
Microagility
4.0
4.0 out of 5 stars
Remote
Contract

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Skills

Data pipelines

Kubernetes

Google Cloud Platform
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Job details
Here’s how the job details align with your profile.
Job type

Contract
 
Full job description
Summary:
Responsible for deploying, monitoring, and maintaining machine learning models in production. Ensures the reliability, scalability, and performance of AI/ML pipelines.

Key Responsibilities:
- Design and implement CI/CD pipelines for ML workflows.
- Manage model versioning, testing, and deployment.
- Monitor model performance and retrain as needed.
- Optimize infrastructure for cost and speed.
- Collaborate with data scientists, engineers, and DevOps teams.

Required Skills:
- Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
- Experience with cloud platforms (AWS, Azure, GCP).
- Knowledge of containerization (Docker, Kubernetes).
- Familiarity with MLOps tools (MLflow, Kubeflow, SageMaker).
- Strong understanding of data pipelines and APIs.

Experience:
3–5 years in machine learning or DevOps, with MLOps experience preferred.

Job Type: Contract

Work Location: Remote

 
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