RunOps Support – MLOps

Required Skills

MLflow
Seldon
Azure ML
SageMaker
CI/CD
Kubernetes
Docker

Job Description

Job Title: RunOps Support – ML Ops

Job Type: Full-Time

Location: Remote


Job Summary:

We are seeking a proactive and skilled RunOps Support Engineer specializing in ML Ops for remote work. In this role, you will be responsible for the seamless deployment, monitoring, and maintenance of machine learning models in production environments. Your expertise will facilitate the automation of workflows and ensure the reliability of ML pipelines, addressing runtime issues and optimizing performance.


Key Responsibilities:

• Monitor model serving systems and address performance or latency issues.

• Ensure ML pipelines run as scheduled and scale appropriately.

• Support model retraining, deployment, and rollback processes.

• Collaborate with Data Scientists and ML Engineers on productionizing ML workflows.

• Maintain observability tools and logs for model health tracking.

• Assist in automating workflows and handling model versioning.

• Resolve runtime issues across ML pipelines.


Required Skills and Qualifications:

• 2+ years in ML Ops or platform operations for ML systems.

• Familiarity with model deployment tools such as MLflow, Seldon, SageMaker, or Azure ML.

• Experience with Docker, Kubernetes, and monitoring ML workflows.

• Understanding of CI/CD pipelines in the ML lifecycle.

• Excellent written and verbal communication skills.

• Strong problem-solving skills with attention to detail.


Preferred Qualifications:

• Experience with Vertex AI or similar platforms.

• Background in software engineering or data science.

• Proven track record in a remote or hybrid work environment.

Apply now

Please note that after completing the interview process, you’ll be added to our talent pool and considered for this and other roles that match your skills.

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