Mlops Engineer Jobs in New York
Mlops Engineer jobs in New York are among the most active in the country, concentrated in financial services, media, healthcare technology, and enterprise software, with openings from entry-level ML infrastructure roles through senior and staff-level positions. The heaviest hiring is in New York City, with additional demand in Buffalo and Albany tied to health systems and state government modernization efforts. Major employers with a lasting presence include JPMorgan Chase, IBM, and Memorial Sloan Kettering, and the most sought-after specialties are model deployment pipelines, Kubernetes-based orchestration, and LLMOps for large language model workflows. Find a role that fits below and apply directly.
Find Mlops Engineer JobsOverview
Showing 5 of 17+ Mlops Engineer jobs
Key Responsibilities
AI/ML Model Operations:
- Deploy, manage, and monitor machine learning and AI models in production environments.
- Implement model performance monitoring including accuracy, latency, and inference metrics.
- Detect and mitigate concept drift, data drift, and model degradation.
AI Observability:
- Design and implement AI observability frameworks to track model behavior and reliability.
- Monitor LLM outputs, hallucination rates, and response quality.
- Implement logging, tracing, and evaluation pipelines for AI systems.
Agentic Systems Monitoring:
- Monitor agent-based AI workflows and autonomous systems.
- Track agent actions, tool usage, decision paths, and execution outcomes.
- Implement guardrails, safety monitoring, and failure detection for AI agents.
Data Pipeline Monitoring:
- Monitor and maintain data ingestion, transformation, and feature pipelines.
- Ensure data quality, schema consistency, and pipeline reliability.
- Detect and resolve pipeline failures and anomalies.
Infrastructure & Automation:
- Build and maintain CI/CD pipelines for ML models and AI systems.
- Manage model versioning, experiment tracking, and reproducibility.
- Automate monitoring alerts, incident response, and remediation.
Collaboration:
- Work closely with data scientists, ML engineers, platform teams, and product teams.
- Support continuous improvement of AI system reliability and governance.
Compensation, Benefits and Duration
Minimum Compensation: USD 50,000
Maximum Compensation: USD 177,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.
This position is not available for independent contractors.
No applications will be considered if received more than 120 days after the date of this post.
Key Responsibilities
AI/ML Model Operations:
- Deploy, manage, and monitor machine learning and AI models in production environments.
- Implement model performance monitoring including accuracy, latency, and inference metrics.
- Detect and mitigate concept drift, data drift, and model degradation.
AI Observability:
- Design and implement AI observability frameworks to track model behavior and reliability.
- Monitor LLM outputs, hallucination rates, and response quality.
- Implement logging, tracing, and evaluation pipelines for AI systems.
Agentic Systems Monitoring:
- Monitor agent-based AI workflows and autonomous systems.
- Track agent actions, tool usage, decision paths, and execution outcomes.
- Implement guardrails, safety monitoring, and failure detection for AI agents.
Data Pipeline Monitoring:
- Monitor and maintain data ingestion, transformation, and feature pipelines.
- Ensure data quality, schema consistency, and pipeline reliability.
- Detect and resolve pipeline failures and anomalies.
Infrastructure & Automation:
- Build and maintain CI/CD pipelines for ML models and AI systems.
- Manage model versioning, experiment tracking, and reproducibility.
- Automate monitoring alerts, incident response, and remediation.
Collaboration:
- Work closely with data scientists, ML engineers, platform teams, and product teams.
- Support continuous improvement of AI system reliability and governance.
Compensation, Benefits and Duration
Minimum Compensation: USD 50,000
Maximum Compensation: USD 177,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.
This position is not available for independent contractors.
No applications will be considered if received more than 120 days after the date of this post.
See All 17 Mlops Engineer Jobs in New York
Find roles in New York that match your experience and apply in just a few clicks.
Find Mlops Engineer JobsMlops Engineer Jobs by City in New York
Where New York roles are concentrated, by current openings.
Mlops Engineer Job Market in New York
A snapshot from current New York openings, updated as new roles post.
Who's Hiring
- The New York Times5
- New York Life2
- Alvarez & Marsal1
- Arlo1
- Bloomberg1
Top Industries Hiring
- Technology & Software7
- Media & Entertainment4
- Insurance2
- Accounting & Auditing1
- Consulting & Professional Services1
What New York Employers Look For
The qualifications that appear most often in mlops engineer jobs across New York.
- Proficiency in Python and experience building end-to-end ML pipelines
- Hands-on experience with container orchestration platforms such as Kubernetes and Docker
- Familiarity with cloud environments, particularly AWS, GCP, or Azure ML services
- Experience with CI/CD tooling adapted for machine learning workflows and model versioning
- Knowledge of monitoring and observability tools for deployed models in production environments
- Bachelor's degree in computer science, data engineering, or a closely related technical field
Mlops Engineer Jobs in New York: Frequently Asked Questions
How do you become a mlops engineer in New York?
There is no state-issued license or registration required to work as a mlops engineer in New York. The typical path starts with a degree in computer science, data science, or software engineering, followed by practical experience in software deployment and machine learning workflows. New York employers, particularly in financial services and healthcare tech, strongly favor candidates who have built and maintained production ML systems, and cloud certifications from AWS or Google Cloud consistently strengthen a candidate's profile.
Which companies hire mlops engineers in New York?
Employers hiring mlops engineers in New York right now include The New York Times, New York Life, and Alvarez & Marsal, based on current listings on Migrate Mate as of June 2026. New York's financial services sector, anchored by large banks and asset managers headquartered in Manhattan, drives a significant share of demand for mlops engineers focused on risk modeling and fraud detection pipelines.
Which New York cities have the most mlops engineer jobs?
New York account for the most mlops engineer openings in New York. New York City dominates by a wide margin because of its density of fintech firms, media companies, and large enterprise tech operations, while Buffalo and Albany see demand from regional health systems and state agency technology modernization programs that have expanded their data science infrastructure in recent years.
Are there remote mlops engineer jobs in New York?
Yes, and more than most fields. About 41% of mlops engineer openings tied to New York are remote or hybrid as of June 2026, reflecting how much of the work centers on code, pipelines, and cloud environments rather than physical hardware. The roles most likely to stay fully remote are those focused on model monitoring, pipeline automation, and LLMOps, while positions requiring close collaboration with on-site data science teams more often expect hybrid schedules.
How can I get hired as a mlops engineer in New York with little or no experience?
The most realistic entry path is moving laterally from a software engineering or data engineering role where you have already worked with production systems and automated workflows. New York employers such as large financial institutions and health technology companies often hire associate ML engineers or platform engineers who then transition into dedicated mlops responsibilities. Building a public portfolio of deployment projects using open-source tools and earning an AWS or Google Cloud associate certification gives candidates without formal mlops experience a concrete edge when applying.
Where can I find and apply to mlops engineer jobs in New York?
You can find and apply to mlops engineer jobs in New York on Migrate Mate, which lists current openings from employers hiring in New York right now. Find the roles that match your experience and apply directly from the listing.
See All 17 Mlops Engineer Jobs in New York
Find roles in New York that match your experience and apply in just a few clicks.
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