Overview
Remote
50 - 60
Accepts corp to corp applications
Contract - W2
Contract - 12 Month(s)
No Travel Required
Unable to Provide Sponsorship
Skills
ML models
Python
SQL
MLOPs
Data pipelines
Job Details
Role: Senior MLOps Engineer
Role Description
Design, build, and operate production-grade ML platforms and pipelines, enabling reliable deployment, monitoring, and lifecycle management of machine learning models at scale. The role focuses on operational excellence, automation, and ML system reliability.
Must-Have Skills
- Experience in software/data/ML engineering and operating ML models in production.
- Strong Python (and SQL) skills.
- Hands-on experience with end-to-end ML pipelines (training → deployment → monitoring).
- Solid understanding of MLOps practices: CI/CD for ML, model versioning, monitoring, retraining.
- Experience building and operating distributed systems and data pipelines.
Good-to-Have Skills
- Cloud-native ML platforms (AWS/Azure/Google Cloud Platform).
- Docker & Kubernetes for ML workloads.
- Infrastructure as Code (Terraform / CloudFormation).
- MLOps tools: MLflow, Kubeflow, Airflow.
- ML observability, data/model drift detection, and security/compliance awareness.
- Experience mentoring engineers and influencing architecture decisions.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.