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Full Time Machine Learning Ops Engineer Jobs (NOW HIRING)

Jane Street

Machine Learning Engineer

New York, NY · On-site

... Machine Learning Engineer while also providing a truly unparalleled educational experience ... You'll be paired with full-time employees who act as mentors, collaborating with you on real-world ...

Eccalon LLC

Machine Learning Engineer

Detroit, MI

Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the Research and Development Team, where ...

Capital One

Lead Machine Learning Engineer

San Jose, CA · On-site +1

$120K - $158K/yr

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ... The minimum and maximum full-time annual salaries for this role are listed below, by location.

New

Capital One

Lead Machine Learning Engineer

San Francisco, CA · On-site +1

$120K - $159K/yr

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ... The minimum and maximum full-time annual salaries for this role are listed below, by location.

Capital One

Lead Machine Learning Engineer

Cambridge, MA · On-site +1

$112K - $147K/yr

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ... The minimum and maximum full-time annual salaries for this role are listed below, by location.

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ... The minimum and maximum full-time annual salaries for this role are listed below, by location.

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ... The minimum and maximum full-time annual salaries for this role are listed below, by location.

Capital One

Lead Machine Learning Engineer

Manhattan, NY · On-site +1

$112K - $148K/yr

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ... The minimum and maximum full-time annual salaries for this role are listed below, by location.

Capital One

Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ... The minimum and maximum full-time annual salaries for this role are listed below, by location.

Beyond SOF

Engineer, Machine Learning

Washington, DC · On-site

The Machine Learning Engineer is responsible for developing and implementing machine learning models and algorithms to solve complex problems. Main Responsibilities and Duties: Develop and implement ...

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Full Time Machine Learning Ops Engineer information

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$31.5K

$128.8K

$193.5K

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

As of Jul 10, 2026, the average yearly pay for full time machine learning ops engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI systems, and while AI automation can handle certain tasks, MLEs are essential for creating, optimizing, and troubleshooting complex models. AI tools may augment their work, but the role requires expertise in data science, programming, and system integration that cannot be fully replaced by AI itself.

How much do MLOps engineers make?

MLOps engineers typically earn between $100,000 and $150,000 annually, with salaries increasing based on experience, location, and expertise in tools like Kubernetes, Docker, and cloud platforms. Senior roles or those with specialized skills can exceed $180,000 per year.

What is the difference between Full Time Machine Learning Ops Engineer vs Data Scientist?

AspectFull Time Machine Learning Ops EngineerData Scientist
Primary focusDeploying, maintaining, and optimizing ML models in production environmentsAnalyzing data, building models, and deriving insights
Required skillsMachine learning deployment, cloud platforms, scripting, DevOps practicesStatistical analysis, data visualization, programming (Python/R)
Work environmentProduction systems, cloud infrastructure, cross-functional teamsResearch, data analysis, model development in labs or offices
Common certificationsCloud certifications (AWS, GCP), ML Ops certificationsData science certifications, statistical courses

While both roles involve machine learning, the Full Time Machine Learning Ops Engineer focuses on deploying and maintaining models in production, requiring DevOps and cloud skills. Data Scientists primarily analyze data and develop models, often working in research settings. Understanding these differences helps in choosing the right career path or job focus.

What engineer makes $500,000 a year?

A senior or lead machine learning operations (MLOps) engineer with extensive experience, specialized skills in deploying and maintaining machine learning systems, and working at large tech companies or in high-demand industries can earn $500,000 or more annually. Compensation often includes base salary, bonuses, and stock options, especially in competitive markets or executive-level roles.

Are MLOps engineers in demand?

MLOps engineers are in high demand due to the increasing adoption of machine learning models in various industries. Companies seek professionals skilled in deploying, monitoring, and maintaining ML systems using tools like Docker, Kubernetes, and cloud platforms, making this a growing and competitive field for job seekers.
More about Full Time Machine Learning Ops Engineer jobs
What cities are hiring for Full Time Machine Learning Ops Engineer jobs? Cities with the most Full Time Machine Learning Ops Engineer job openings:
What are the most commonly searched types of Machine Learning Ops Engineer jobs? The most popular types of Machine Learning Ops Engineer jobs are:
What states have the most Full Time Machine Learning Ops Engineer jobs? States with the most job openings for Full Time Machine Learning Ops Engineer jobs include:
What job categories do people searching Full Time Machine Learning Ops Engineer jobs look for? The top searched job categories for Full Time Machine Learning Ops Engineer jobs are:
Full Time Machine Learning Ops Engineer jobs near you
Infographic showing various Full Time Machine Learning Ops Engineer job openings in the United States as of July 2026, with employment types broken down into 95% Full Time, 2% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.
Machine Learning Engineer

Machine Learning Engineer

Jane Street

New York, NY • On-site

Full-time

Re-posted 4 days ago

Job description

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'll be paired with full-time employees who act as mentors, collaborating with you on real-world ML projects we actually need done. Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques.
Machine learning is a critical pillar of Jane Street's global business. Our ever-changing trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas with relatively little friction. If you'd like to learn more, you can have a look at our Machine Learning page.
During the program, you'll work on projects mentored closely by the full-time employees who designed them. Some projects consider big-picture questions that we're still trying to figure out, while others involve building something new. You will get access to our growing GPU cluster containing thousands of H100/H200/B200s and gain an understanding of the differences between textbook machine learning and its application to noisy financial data.
The interview process follows the same structure as our Software Engineering Intern interviews, with one key addition: after your initial technical coding interview over Zoom, you'll have an on-site interview with 2-4 technical rounds, including 1-2 dedicated to assessing ML engineering skills.
Learn more about Jane Street's internship program here.
About You
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. If you have a curious mind, a collaborative spirit, and a passion for solving interesting problems, we have a feeling you'll fit right in. We don't expect you to have a background in finance-we're more interested in how you think and learn than what you currently know. You should be:
  • An undergraduate or PhD student with practical experience training an ML model, working on an ML library, or optimizing an ML workflow
  • A top-notch programmer with a love for technology
  • Intellectually curious, collaborative, and eager to learn
  • Humble and unafraid to ask questions and admit mistakes

Apply