ML Engineer / AI Operations-2
Role summary
This role is for an ML Engineer focused on AI Operations, based in Morristown, NJ. The primary responsibility is to own and operate the CI/CD pipelines for existing ML services, ensuring robust deployment strategies like blue/green and canary releases with automated rollbacks. The engineer will manage model and data drift monitoring, set up alerts, and build production dashboards and incident workflows. Key duties include providing L2/L3 support for production ML systems, performing root-cause analysis, and documenting operational procedures. The role also involves hardening research notebooks into production-ready services and ensuring seamless integration of ML models into various enterprise systems and observability stacks.
Morristown, New Jersey 07960 Posted April 4th, 2026
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Job Type: Full Time
Job Category: IT
Job Description
Job Title : ML Engineer - AI Operations
Location : Morristown, NJ (Onsite)
Fulltime
Skill: ML Engineer - AI Operations
Key responsibilities:
Own and operate CI/CD for existing ML services across dev/test/prod; standardize blue/green and canary releases with automated rollbacks.
Run model/data drift and performance monitoring with SLAs; define alerts, thresholds, and retraining triggers.
Build and maintain production dashboards, alerts, and incident workflows; codify on-call runbooks and escalation paths.
Partner with onshore model owners to diagnose metric degradation and land mitigations aligned to governance and controls.
Provide day-to-day L2/L3 support for production ML: triage, root-cause analysis, permanent fixes, and post-incident reviews.
Own operational documentation: runbooks, standard operating procedures, and recurring health checks.
Coordinate hotfixes and safe rollbacks with onshore teams; verify recovery via automated smoke tests.
Harden and productionize research notebooks into maintainable, testable services with CI, unit/integration tests, and linting.
Operate and evolve model-serving APIs and batch scoring jobs; integrate with enterprise schedulers and data platforms.
Ensure models are fully integrated into CI/CD, observability, and monitoring stacks; enforce traceability with experiment and model registries.
Validate successful delivery of model outputs to apps, chatbots, reports, and downstream systems with contract tests and data quality checks.
Required Skills:
Git/GitLab, Python, SQL, MLflow, Power BI, Snowflake.
OLAP/OLTP data modeling and architecture.
API frameworks (FastAPI/Flask), and
Nice to have:
Modern ELT tools (Fivetran/Airbyte).
Streaming/real-time data pipelines (e.g., Kafka, Kinesis, Redpanda).
Production ML service operations experience (experience in broader full-stack environments is a plus.
Required Skills
DEVOPS ENGINEER
SENIOR EMAIL SECURITY ENGINEER