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Machine Learning Ops Engineer Jobs in New York (NOW HIRING)

Moody's Analytics

MLOps Engineer

New York, NY · On-site +1

As the Machine Learning Ops Engineer for the AI Team you will: * Work closely with the Data Science team and the Data Engineers and DevOps teams in order to deploy machine learning models.

Forhyre

Machine Learning Engineer

New York, NY

We are looking for a Machine Learning Engineer to help us create artificial intelligence products. Machine Learning Engineer responsibilities include creating machine learning models and retraining ...

Capital One

Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

About the Position Our goals are to give you a real sense of what it's like to work at Jane Street as a Machine Learning Engineer while also providing a truly unparalleled educational experience. You ...

Jane Street

Machine Learning Engineer

New York, NY

About the Position Our goals are to give you a real sense of what it's like to work at Jane Street as a Machine Learning Engineer while also providing a truly unparalleled educational experience. You ...

Hang

Machine Learning Engineer

New York, NY · On-site +1

About the Role We are seeking a skilled and innovative Machine Learning Engineer to join our team. This person will implement and develop machine learning models to enhance our platform ...

Capital One

Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ...

Zencastr

Senior Machine Learning Engineer (Remote)

New York, NY · On-site +1

$114K - $157K/yr

We are looking for an outstanding machine learning engineer to join our team! The role will provide ... Good dev ops experience * Advanced DSP experience * MongoDB or SQL experience * Experience with ...

Capital One

Lead Machine Learning Engineer

New York, NY · On-site

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ...

Capital One

Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ...

Point72

Machine Learning Engineer

New York, NY · On-site

We are seeking a Machine Learning Engineer to join the High Frequency Trading Technology team. This role will apply the latest AI technologies to solve various real-world problems and streamline day ...

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Machine Learning Ops Engineer information

See New York salary details

$34.5K

$140.9K

$211.7K

How much do machine learning ops engineer jobs pay per year?

As of Jul 25, 2026, the average yearly pay for machine learning ops engineer in New York is $140,878.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $169,600.00 per year, depending on experience, location, and employer.

What is a Machine Learning Ops Engineer job?

A Machine Learning Ops Engineer (MLOps Engineer) focuses on deploying, monitoring, and maintaining machine learning models in production. They bridge the gap between data science and software engineering, ensuring models run efficiently, reliably, and at scale. Their responsibilities include automating workflows, managing infrastructure, and ensuring CI/CD pipelines for ML models. They work with tools like Kubernetes, Docker, and cloud platforms to streamline model deployment. Ultimately, an MLOps Engineer ensures that machine learning models are operationalized and continuously improved in a real-world environment.

What does a typical day look like for a Machine Learning Ops Engineer?

A typical day for a Machine Learning Ops Engineer involves collaborating with data scientists to streamline the deployment of models, building and maintaining scalable infrastructure on cloud services, and automating workflows with CI/CD tools. You may troubleshoot issues in production environments, monitor model performance, and implement solutions for model versioning and retraining. Often, you’ll work closely with software engineers, DevOps teams, and data analysts to ensure seamless integration of machine learning solutions into products. This cross-functional role keeps you engaged with cutting-edge technology and provides opportunities to influence both technical and business outcomes.

What are the key skills and qualifications needed to thrive in the Machine Learning Ops Engineer position, and why are they important?

To thrive as a Machine Learning Ops Engineer, you need a solid grasp of machine learning concepts, cloud platforms, software engineering, and DevOps practices, typically supported by a degree in computer science or a related field. Experience with tools like Docker, Kubernetes, TensorFlow, CI/CD pipelines, and certifications such as AWS Certified Machine Learning – Specialty are highly valuable. Strong problem-solving skills, communication, and the ability to work collaboratively across data science and engineering teams set top candidates apart. These skills ensure reliable deployment, scalability, and optimization of machine learning models in production environments.

What are the most commonly searched types of Machine Learning Ops Engineer jobs in New York? The most popular types of Machine Learning Ops Engineer jobs in New York are:
What are popular job titles related to Machine Learning Ops Engineer jobs in New York? For Machine Learning Ops Engineer jobs in New York, the most frequently searched job titles are:
What job categories do people searching Machine Learning Ops Engineer jobs in New York look for? The top searched job categories for Machine Learning Ops Engineer jobs in New York are:
Machine Learning Ops Engineer jobs near you
Infographic showing various Machine Learning Ops Engineer job openings in New York as of July 2026, with employment types broken down into 93% Full Time, 4% Part Time, and 3% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $140,878 per year, or $67.7 per hour.

MLOps Engineer

Moody's Analytics

New York, NY • On-site, Remote

Full-time

Posted 13 days ago

Job description

In the Predictive Analytics AI group, we build data-driven, highly distributed machine learning systems. Our engineers and researchers are responsible for architecting and developing these ML services end-to-end overcoming unique challenges that involve building systems that have high throughput availability, consistency, and low latency. The Predictive Analytics AI Group is the central group in Moody's Analytics comprising of researchers and engineers working together to build data-driven customer-facing products, as well as the necessary infrastructure to support the ML services following the industry leading practices. The group has worked on and built some award-winning AI products like Compliance Catalyst, Adverse Media Monitoring, Coronapulse, Quiqspread, News Edge 2.0, ESG and has participated in various internal automation initiatives. The group also regularly publish and present their work in top-tier academic and industry conferences. We have a flexible work environment and allow remote work depending on one's personal choice.


Responsibilities:

As the Machine Learning Ops Engineer for the AI Team you will:

  • Work closely with the Data Science team and the Data Engineers and DevOps teams in order to deploy machine learning models. Specifically execute continuous integration and continuous delivery (CI/CD) activities to release ML code and ML pipelines into a Production environment
  • Maintain the Machine Learning pipeline and make sure everything is running accurately and reliably
  • Liaise with senior stakeholders across the Data function and the wider business
  • Use industry best practices such as code reviews, pull requests, and peer testing to ensure high quality AI/ML deliverables
  • Build AI/ML model performance benchmarking, evaluation, monitoring capabilities and facilitates resolution of issues with the appropriate teams

SKILLS AND EXPERIENCE


Must Have:

  • Proven industry/commercial/research lab experience (2+ years) deploying machine learning models and maintaining ML pipelines, orchestration, deployment, monitoring, & support
  • Experience creating and maintaining deployment pipelines with CI/CD tools (2+ years)
  • Knowledge of cloud technologies (e.g. AWS) and Extensive Programming experience in Python & SQL
  • Experience in containerization and orchestration (such as Docker, Kubernetes)
  • Practical Knowledge of Machine Learning models in commercial settings
  • Good communication skills

Nice to Have:

  • Experience building batch and/or real-time data & ML pipelines
  • Familiarity with MLflow (or similar platforms like Kubeflow and other tools)
  • Promotes a practice of unifying system development (Dev) and system operations (Ops)

Employment Type: FULL_TIME

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