What is an MLOps Engineer?

Last updated: February 8, 2026Reviewed date: February 8, 2026Reading time: 6 min read
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MLOps is the next evolution of operations. It's a new way of approaching your day-to-day operations that can make it much easier to manage and more efficient for your team. MLOps is about streamlining your organization's processes, automating those processes, and ensuring that you're using...

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Article Summary

MLOps is the next evolution of operations. It's a new way of approaching your day-to-day operations that can make it much easier to manage and more efficient for your team. MLOps is about streamlining your organization's processes, automating those processes, and ensuring that you're using the right tools correctly. It's about taking the time to understand your team's needs and making them happen. What is...

Key Takeaways

  • This article explains What is an MLOps Engineer? in simple medical language.
  • This article explains Difference Between Data Scientist & MLOps Engineer in simple medical language.
  • This article explains MLOps Engineer Job Role in simple medical language.
  • This article explains MLOps Engineer Roles and Responsibilities in simple medical language.
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Definition

MLOps is the next evolution of operations.

It’s a new way of approaching your day-to-day operations that can make it much easier to manage and more efficient for your team.

MLOps is about streamlining your organization’s processes, automating those processes, and ensuring that you’re using the right tools correctly. It’s about taking the time to understand your team’s needs and making them happen.

What is an MLOps Engineer?

MLOps Engineers are the people who build, maintain, and optimize machine learning solutions. They are the ones who ensure that your algorithms are performing as expected.

They are also responsible for building new models and improving existing ones.

They have a wide range of skills, including knowledge of data science, software engineering, and domain expertise in the industry in which they work.

They also need to be able to understand business problems and come up with solutions to them using machine learning techniques.

Difference Between Data Scientist & MLOps Engineer

There are many parallels between the roles of a data scientist and an MLOps engineer, but there are also some key differences.

Both positions require a deep understanding of machine learning and artificial intelligence and the ability to implement those technologies in an enterprise setting.

However, data scientists focus more on research and development, while MLOps focuses on production.

The difference between these two roles is subtle but essential:

  • Data scientists often spend more time thinking about what could be done than actually doing it.
  • MLOps engineers spend more time doing than thinking (but still think about how things could be done).
  • Data scientists may be tasked with developing new models or algorithms for solving specific problems, but they only sometimes work directly with the code that implements those models.
  • MLOps engineers generally do develop code that runs in production environments—they are responsible for implementing new models or algorithms in ways that real-world systems can use.

MLOps Engineer Job Role

The MLOps Engineer will work with the data science team to develop and maintain a platform that automates creating, training, deploying and updating machine learning models.

The MLOps engineer will have extensive knowledge of Apache Spark, Scala, and Python and will have experience building large-scale data pipelines using Apache Kafka.

The MLOps Engineer should be able to work independently and in a team environment and be passionate about creating highly scalable, efficient, and easy-to-maintain solutions.

MLOps Engineer Roles and Responsibilities

The MLOps Engineer is responsible for ensuring that ML engineers can scale the machine learning models across the entire organization. They are responsible for building and maintaining the infrastructure that will allow this scaling to occur.

They also ensure that data scientists can use these models without having to worry about how they’re built or maintained.

An MLOps Engineer is a person who designs, builds, and runs machine learning systems at scale.

They are responsible for maintaining the infrastructure that supports the models and algorithms that power the products of their company, including:

  • Monitoring the performance of these systems
  • Identifying ways to improve their performance
  • Investigating issues when they arise

They also monitor the performance of your models, and they need to be able to troubleshoot any errors or bugs that may occur.

In addition to these responsibilities, an MLOps Engineer might be tasked with improving your model’s accuracy by tweaking its parameters or updating the data it uses for training.

MLOps Engineer Skills

MLOps Engineers are the bridge between machine learning and operations. They ensure that the machine learning models are being deployed and updated correctly, not causing any problems.

MLOps needs to have the following skills:

  • Have experience working in an agile environment
  • Be a problem solver and quick learner
  • Understand the importance of continuous learning and personal development
  • Demonstrate knowledge of at least one programming language, preferably Python or Java.

They also need to interpret the results of their models, which means they need to be able to read data on a fundamental level and understand how it relates to the problem being solved by the model.

The technical skills you need to be an MLOps engineer are:

  • Data Science
  • Statistical modeling
  • Python/R programming
  • Machine learning (ML)
  • SQL
  • Linux/Unix shell scripting

MLOps Engineer Salary

Salary in the US

If you’re looking to make a career change or want to make more money, MLOps Engineering might be the right choice.

According to Glassdoor, the national average salary for an MLOps Engineer is $94,608 annually.

Salary in India

You can make a lot of money as an MLOps Engineer.

If you’re looking for a new job or thinking about retraining and returning to school, consider learning how to be an MLOps Engineer. The average salary for this job is ₹10,48,920 in India.

MLOps Engineer Job Outlook

The job outlook for MLOps engineers is strong. The field of machine learning and operations, or MLOps, is still new and multiplying. As more companies automate specific processes, there will be a need for people who can ensure that these processes are working as intended.

MLOps engineers are in high demand because they can solve problems at a time when many companies are still trying to figure out how to use machine learning effectively.

The Bureau of Labor Statistics predicts that there will be a 21% increase in jobs for MLOps engineers between now and 2024, which is higher than average for all careers in this field.

Conclusion

At Simplilearn, we’re all about helping you succeed. That’s why we created this program with Caltech University and IBM, to give you the skills you need to stand out in AI and Machine Learning.

Caltech Post Graduate Program In AI And Machine Learning is designed after our intense learning model, which means that it’s rigorous and challenging but also rewarding. You’ll learn how to apply advanced algorithms to solve problems in your industry and how to use the most advanced AI applications on the market today.

This program is for you if you want to elevate your AI and Machine Learning expertise.

FAQs

1. What is an MLOps engineer?

An MLOps engineer is a developer who focuses on the operations and management of machine learning models, algorithms, and processes. They work with data scientists to help make sure that their projects are being used effectively, and they monitor the health of the models they create.

2. What is the job of MLOps?

The job of MLOps is to help the company build and maintain an ML platform that supports the company’s goals. They create pipelines for data to flow through, train models, and set up applications.

MLOps are often responsible for ensuring their systems are running smoothly, but they can also work on projects like improving the model or design itself.

3. Is MLOps a data engineer?

No, MLOps is not a data engineer.

A data engineer specializes in the development and deployment of data-driven applications. They typically work with structured data stored in databases and structured files. They focus on ensuring that information is available to others who need access.

4. What is MLOps vs. DevOps?

DevOps and MLOps are two different processes that can improve your company’s operations. DevOps is a process that focuses on the development side of things, while MLOps is a process that focuses on the machine learning side.

5. Do I need to learn DevOps for MLOps?

Yes, you do.

As the name suggests, DevOps is about creating software for an organization. MLOps is about using machine learning to help an organization make better decisions.

6. How do I learn MLOps?

You can learn MLOps through several methods:

  • Self-study
  • Courses
  • Online courses
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Safety note: This is not a prescription or diagnosis. For severe symptoms, pregnancy danger signs, children with serious illness, chest pain, breathing difficulty, stroke-like weakness, or major injury, seek urgent care.

Which doctor may help?

Start with a registered doctor or the nearest qualified health center.

What to tell the doctor

  • Write when the problem started and how it changed.
  • Bring old prescriptions, investigation reports, and current medicines.
  • Write allergies, pregnancy status, diabetes, kidney/liver disease, and major past illnesses.
  • Bring one family member if the patient is weak, elderly, confused, or a child.

Questions to ask

  • What is the most likely cause of my symptoms?
  • Which danger signs mean I should go to hospital quickly?
  • Which tests are necessary now, and which can wait?
  • How should I take medicines safely and what side effects should I watch for?
  • When should I come for follow-up?

Tests to discuss

  • Vital signs: temperature, pulse, blood pressure, oxygen saturation
  • Basic physical examination by a clinician
  • CBC, urine test, blood sugar, or imaging only when clinically needed

Avoid these mistakes

  • Do not use antibiotics, steroid tablets/injections, or strong painkillers without proper medical advice.
  • Do not hide pregnancy, kidney disease, ulcer, allergy, or blood thinner use.
  • Do not delay emergency care when danger signs are present.

Medicine safety and first-aid guide

This section is for patient education only. It does not replace a doctor, pharmacist, or emergency care.

Safe first steps

  • Rest, drink safe water, and observe symptoms carefully.
  • Keep a written note of symptoms, duration, temperature, medicines already taken, and allergy history.
  • Seek medical care quickly if symptoms are severe, worsening, or unusual for the patient.

OTC medicine safety

  • For mild pain or fever, ask a registered pharmacist or doctor before using common over-the-counter pain/fever medicines.
  • Do not combine multiple pain medicines without advice, especially if you have kidney disease, liver disease, stomach ulcer, asthma, pregnancy, or take blood thinners.
  • Do not give adult medicines to children unless a qualified clinician advises it.

Avoid these mistakes

  • Do not start antibiotics without a proper medical decision.
  • Do not use steroid tablets or injections casually for quick relief.
  • Do not delay emergency care because of home remedies.

Get urgent help if

  • Severe symptoms, confusion, fainting, breathing difficulty, chest pain, severe dehydration, or sudden weakness need urgent medical care.
Medicine names, dose, and timing must be decided by a qualified clinician or pharmacist after checking age, pregnancy, allergy, other diseases, and current medicines.

For rural patients and family caregivers

Patient health record and symptom diary

Write your symptoms, medicines already taken, test results, and questions before visiting a doctor. This note stays on your device unless you print or copy it.

Doctor to discuss: Doctor / qualified healthcare provider
Tests to discuss with doctor
  • Basic vital signs: temperature, pulse, blood pressure, oxygen level if needed
  • Relevant blood, urine, imaging, or specialist tests only after clinical assessment
Questions to ask
  • What is the most likely cause of my symptoms?
  • Which warning signs mean I should go to emergency care?
  • Which tests are really needed now?
  • Which medicines are safe for my age, pregnancy status, allergy, kidney/liver/stomach condition, and current medicines?

Emergency warning signs such as chest pain, severe breathing difficulty, sudden weakness, confusion, severe dehydration, major injury, or loss of bladder/bowel control need urgent medical care. Do not wait for online information.

Safe pathway to proper treatment

Care roadmap for: What is an MLOps Engineer?

Use this simple roadmap to understand the next safe steps. It is educational and does not replace examination by a doctor.

Go to emergency care if you notice:
  • Severe or rapidly worsening symptoms
  • Breathing difficulty, chest pain, fainting, confusion, severe weakness, major injury, or severe dehydration
Doctor / service to discuss: Qualified healthcare provider; specialist depends on symptoms and examination.
  1. Step 1

    Check danger signs first

    If danger signs are present, seek emergency care and do not wait for online information.

  2. Step 2

    Record the symptom story

    Write when symptoms started, severity, medicines already taken, allergies, pregnancy status, and test results.

  3. Step 3

    Visit a qualified clinician

    A doctor, nurse, or qualified healthcare provider can examine you and decide which tests or treatment are needed.

  4. Step 4

    Do only useful tests

    Do tests after clinical assessment. Avoid unnecessary tests, random antibiotics, or repeated medicines without diagnosis.

  5. Step 5

    Follow up and return early if worse

    If symptoms worsen, new warning signs appear, or treatment is not helping, return for review quickly.

Rural patient practical tips
  • Take a written symptom diary and all previous prescriptions/test reports.
  • Do not hide medicines already taken, even herbal or over-the-counter medicines.
  • Ask which warning signs mean urgent referral to hospital.

This roadmap is for education. A real diagnosis and treatment plan requires history, examination, and clinical judgment.

RX Patient Help

Ask a health question safely

Write your symptom story. A health professional or site editor can review it before any answer is prepared. This box is not for emergency care.

Emergency first: Severe chest pain, breathing trouble, unconsciousness, stroke signs, severe injury, heavy bleeding, or rapidly worsening symptoms need urgent local medical care now.

Frequently Asked Questions

What is an MLOps Engineer?

MLOps Engineers are the people who build, maintain, and optimize machine learning solutions. They are the ones who ensure that your algorithms are performing as expected. They are also responsible for building new models and improving existing ones. They have a wide range of skills, including knowledge of data science, software engineering, and domain expertise in the industry in which they work. They also need to be able to understand business problems and come up with solutions to them using machine…

Difference Between Data Scientist & MLOps Engineer There are many parallels between the roles of a data scientist and an MLOps engineer, but there are also some key differences. Both positions require a deep understanding of machine learning and artificial intelligence and the ability to implement those technologies in an enterprise setting. However, data scientists focus more on research and development, while MLOps focuses on production. The difference between these two roles is subtle but essential: Data scientists often spend more time thinking about what could be done than actually doing it. MLOps engineers spend more time doing than thinking (but still think about how things could be done). Data scientists may be tasked with developing new models or algorithms for solving specific problems, but they only sometimes work directly with the code that implements those models. MLOps engineers generally do develop code that runs in production environments—they are responsible for implementing new models or algorithms in ways that real-world systems can use. MLOps Engineer Job Role The MLOps Engineer will work with the data science team to develop and maintain a platform that automates creating, training, deploying and updating machine learning models. The MLOps engineer will have extensive knowledge of Apache Spark, Scala, and Python and will have experience building large-scale data pipelines using Apache Kafka. The MLOps Engineer should be able to work independently and in a team environment and be passionate about creating highly scalable, efficient, and easy-to-maintain solutions. MLOps Engineer Roles and Responsibilities The MLOps Engineer is responsible for ensuring that ML engineers can scale the machine learning models across the entire organization. They are responsible for building and maintaining the infrastructure that will allow this scaling to occur. They also ensure that data scientists can use these models without having to worry about how they're built or maintained. An MLOps Engineer is a person who designs, builds, and runs machine learning systems at scale. They are responsible for maintaining the infrastructure that supports the models and algorithms that power the products of their company, including: Monitoring the performance of these systems Identifying ways to improve their performance Investigating issues when they arise They also monitor the performance of your models, and they need to be able to troubleshoot any errors or bugs that may occur. In addition to these responsibilities, an MLOps Engineer might be tasked with improving your model's accuracy by tweaking its parameters or updating the data it uses for training. MLOps Engineer Skills MLOps Engineers are the bridge between machine learning and operations. They ensure that the machine learning models are being deployed and updated correctly, not causing any problems. MLOps needs to have the following skills: Have experience working in an agile environment Be a problem solver and quick learner Understand the importance of continuous learning and personal development Demonstrate knowledge of at least one programming language, preferably Python or Java. They also need to interpret the results of their models, which means they need to be able to read data on a fundamental level and understand how it relates to the problem being solved by the model. The technical skills you need to be an MLOps engineer are: Data Science Statistical modeling Python/R programming Machine learning (ML) SQL Linux/Unix shell scripting MLOps Engineer Salary Salary in the US If you're looking to make a career change or want to make more money, MLOps Engineering might be the right choice. According to Glassdoor, the national average salary for an MLOps Engineer is $94,608 annually. Salary in India You can make a lot of money as an MLOps Engineer. If you're looking for a new job or thinking about retraining and returning to school, consider learning how to be an MLOps Engineer. The average salary for this job is ₹10,48,920 in India. MLOps Engineer Job Outlook The job outlook for MLOps engineers is strong. The field of machine learning and operations, or MLOps, is still new and multiplying. As more companies automate specific processes, there will be a need for people who can ensure that these processes are working as intended. MLOps engineers are in high demand because they can solve problems at a time when many companies are still trying to figure out how to use machine learning effectively. The Bureau of Labor Statistics predicts that there will be a 21% increase in jobs for MLOps engineers between now and 2024, which is higher than average for all careers in this field. Conclusion At Simplilearn, we're all about helping you succeed. That's why we created this program with Caltech University and IBM, to give you the skills you need to stand out in AI and Machine Learning. Caltech Post Graduate Program In AI And Machine Learning is designed after our intense learning model, which means that it's rigorous and challenging but also rewarding. You'll learn how to apply advanced algorithms to solve problems in your industry and how to use the most advanced AI applications on the market today. This program is for you if you want to elevate your AI and Machine Learning expertise. FAQs 1. What is an MLOps engineer?

An MLOps engineer is a developer who focuses on the operations and management of machine learning models, algorithms, and processes. They work with data scientists to help make sure that their projects are being used effectively, and they monitor the health of the models they create.

2. What is the job of MLOps?

The job of MLOps is to help the company build and maintain an ML platform that supports the company's goals. They create pipelines for data to flow through, train models, and set up applications. MLOps are often responsible for ensuring their systems are running smoothly, but they can also work on projects like improving the model or design itself.

3. Is MLOps a data engineer?

No, MLOps is not a data engineer. A data engineer specializes in the development and deployment of data-driven applications. They typically work with structured data stored in databases and structured files. They focus on ensuring that information is available to others who need access.

4. What is MLOps vs. DevOps?

DevOps and MLOps are two different processes that can improve your company's operations. DevOps is a process that focuses on the development side of things, while MLOps is a process that focuses on the machine learning side.

5. Do I need to learn DevOps for MLOps?

Yes, you do. As the name suggests, DevOps is about creating software for an organization. MLOps is about using machine learning to help an organization make better decisions.

6. How do I learn MLOps?

You can learn MLOps through several methods: Self-study Courses Online courses

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