Negotiable
Outside
Remote
USA
Summary: The AI MLOps Platform/DevOps Engineer role involves working with machine learning observability tools and ensuring effective monitoring and support for AI systems. The position is fully remote and is intended for W2 consultants, with a focus on containerization and CI/CD pipelines. Candidates should have a strong background in Python and experience with data drift detection. This is a contract-to-hire opportunity with four openings available.
Key Responsibilities:
- Utilize ML observability tools such as Dynatrace, MLflow, EvidentlyAI, Prometheus, and Grafana.
- Implement data drift detection and statistical monitoring.
- Manage containerization using Docker/Kubernetes and CI/CD pipelines.
- Provide production support and AI monitoring.
- Develop automation and monitoring scripts in Python.
Key Skills:
- Experience with ML observability tools.
- Understanding of data drift detection and statistical monitoring.
- Hands-on experience with containerization (Docker/Kubernetes) and CI/CD pipelines.
- Production support and AI monitoring experience.
- Proficiency in Python for automation and monitoring scripts.
Salary (Rate): undetermined
City: undetermined
Country: USA
Working Arrangements: remote
IR35 Status: outside IR35
Seniority Level: undetermined
Industry: IT
Position: AI MLOps Platform/DevOps Engineer 4 Openings
Location: Long term - Contract to hire (CTH)
Duration: 100% Remote
Only W2 Consultants
Must have Skills
- Experience with ML observability tools (Dynatrace, MLflow, EvidentlyAI, Prometheus, Grafana, etc.).
- Strong understanding of data drift detection and statistical monitoring.
- Hands-on with containerization (Docker/Kubernetes) and CI/CD pipelines.
- Experience in production support and AI monitoring.
- Proficient in Python for automation and monitoring scripts.