ML Engineer
Equiliem
Job Title: ML Engineer - AI Operations
Location: Morristown, NJ (100% Onsite from Day 1)
Duration: 6 Months Primary Skills:
Artificial Intelligence (AI), Google Data Engineering Role Overview
We are seeking an experienced ML Engineer with a strong focus on AI Operations (MLOps) to manage, optimize, and scale production-grade machine learning systems. The ideal candidate will have deep expertise in CI/CD for ML, model monitoring, and production support, ensuring reliability, performance, and governance of deployed models. Key Responsibilities
Location: Morristown, NJ (100% Onsite from Day 1)
Duration: 6 Months Primary Skills:
Artificial Intelligence (AI), Google Data Engineering Role Overview
We are seeking an experienced ML Engineer with a strong focus on AI Operations (MLOps) to manage, optimize, and scale production-grade machine learning systems. The ideal candidate will have deep expertise in CI/CD for ML, model monitoring, and production support, ensuring reliability, performance, and governance of deployed models. Key Responsibilities
- Own and manage end-to-end CI/CD pipelines for ML services across development, testing, and production environments
- Implement and standardize deployment strategies such as blue/green and canary releases with automated rollback mechanisms
- Monitor model performance, data drift, and system health with defined SLAs, alerts, and retraining triggers
- Build and maintain production dashboards, alerting systems, and incident response workflows
- Collaborate with onshore stakeholders to diagnose model degradation and implement corrective actions aligned with governance standards
- Provide L2/L3 production support including triaging issues, root cause analysis, and implementing long-term fixes
- Conduct post-incident reviews and ensure continuous improvement of operational processes
- Develop and maintain operational documentation including runbooks, SOPs, and system health check procedures
- Coordinate hotfix deployments and rollback strategies, ensuring system stability through automated validation tests
- Convert research notebooks into scalable, production-ready services with proper testing, CI integration, and code quality standards
- Manage and enhance model-serving APIs and batch processing pipelines integrated with enterprise data platforms
- Ensure full integration of ML models with CI/CD pipelines, monitoring systems, and experiment tracking tools
- Validate downstream data delivery to applications, chatbots, and reporting systems through contract testing and data quality checks
- Strong experience with Python, SQL, Git/GitLab
- Hands-on expertise with MLflow, Snowflake, Power BI
- Experience in API development (FastAPI / Flask)
- Solid understanding of OLAP/OLTP data modeling and architecture
- Proven experience in production ML systems and MLOps practices
Vacancy posted 5 days ago
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