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

Jane Street

Machine Learning Engineer

New York, NY

We are looking for an engineer with robust experience in machine learning and strong mathematical foundations to join our growing ML team and to help drive the direction of our ML platform. Machine ...

Reddit

Machine Learning Engineer

New York, NY · On-site +1

$223K - $260K/yr

Collaborate closely with multiple stakeholders across product, engineering, research and marketing. Train, evaluate, test, and deploy machine learning models. Part-time telecommuting is an option.

Kitware

Machine Learning Engineer

Minneapolis, MN · On-site

$85K - $125K/yr

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

Virtu Financial

Machine Learning Engineer

New York, NY · On-site

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a small group of technologists whose primary function is building the infrastructure that powers our ...

Virtu Financial

Machine Learning Engineer

New York, NY · On-site

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a small group of technologists whose primary function is building the infrastructure that powers our ...

PhysicsX

Machine Learning Engineer

New York, NY · On-site

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

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All JobsMachine Learning Ops Engineer JobsMachine Learning Ops Engineer Jobs in New York

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 4, 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 June 2026, with employment types broken down into 87% Full Time, 3% Part Time, and 10% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $140,878 per year, or $67.7 per hour.
Machine Learning Engineer

Machine Learning Engineer

Jane Street

New York, NY

Other

Posted 28 days ago

Job description

We are looking for an engineer with robust experience in machine learning and strong mathematical foundations to join our growing ML team and to help drive the direction of our ML platform.

Machine learning is a critical pillar of Jane Street's global business. Our ever-evolving trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas with relatively little friction. Our ML team is full of people with a shared love for the craft of software engineering, and for designing APIs and systems that are delightful to use. 

We'll rely on your in-depth knowledge of the ML ecosystem and understanding of varying approaches - whether it's neural networks, random forests, gradient-boosted trees, or sophisticated ensemble methods - to aid decision-making so we apply the right tool for the problem at hand. Your work will also focus on enhancing research workflows to tighten our feedback cycles. Successful ML engineers will be able to understand the mechanics behind various modeling techniques, while also being able to break down the mathematics behind them.

If you've never thought about a career in finance, you're in good company. Many of us were in the same position before working here. While there isn't a fixed list of qualifications we're looking for, if you have a curious mind and a passion for solving interesting problems, we have a feeling you'll fit right in. 

We're looking for someone with:

  • Experience building and maintaining training and inference infrastructure, with an understanding of what it takes to move from concept to production
  • A strong mathematical background; Good candidates will be excited about things like optimization theory, regularization techniques, linear algebra, and the like
  • A passion for keeping up with the state of the art, whether that means diving into academic papers, experimenting with the latest hardware, or reading the source of a new machine learning package
  • A proven ability to create and maintain an organized research codebase that produces robust, reproducible results while maintaining ease of use
  • Expertise wrangling an ML framework - we're fans of PyTorch, but we'd also love to learn what you know about Jax, TensorFlow, or others
  • An inventive approach and the willingness to ask hard questions about whether we're taking the right approaches and using the right tools

If you're a recruiting agency and want to partner with us, please reach out to agency-partnerships@janestreet.com.

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