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Mlops Machine Learning Engineer Jobs (NOW HIRING)

Quarterhill

Machine Learning Engineer

Frisco, TX · On-site

Overview Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team ... Apply MLOps best practices for training, evaluation, deployment, and monitoring of production grade ...

Leash Bio

Machine Learning Engineer

Salt Lake City, UT · On-site

They are seeking a highly skilled Machine Learning Engineer to manage large datasets, optimize ... Preferred : • Familiarity with common MLops tooling (e.g., Dagster, Prefect, Airflow, Docker ...

Apex Systems

Machine Learning Engineer

Pleasanton, CA · On-site

Leverage MLOps concepts such as CI/CD for ML models, version control, monitoring, automation, and ... Experience with Azure Machine Learning, Azure DevOps, Azure Databricks, or Azure Functions.

Perfict

Machine Learning Engineer

... MLOps • Strong programming skills, preferably in languages like Python, Java, or Scala • Proficiency in machine learning libraries and frameworks, such as TensorFlow, PyTorch, or scikit-learn • ...

FastTek

Machine Learning Engineer

Dearborn, MI · On-site

Machine Learning Engineer #1058742 Position Description: We are seeking an experienced AI Engineer ... This role combines expertise in Data Science, Software Engineering, and MLOps to deliver scalable ...

Sabio infotech

Sr. Machine Learning Engineer

Cincinnati, OH · On-site

$100K - $137K/yr

... frameworks for MLOps, model lifecycle management, monitoring, validation, version control ... machine learning engineering, MLOps, Responsible AI, and production AI systems. Required ...

NT Concepts

Machine Learning Engineer

Chantilly, VA · On-site

$120K - $180K/yr

We are seeking a Machine Learning Engineer with a passion for building mission-critical ... MLOps & Pipeline Automation : Build, maintain, and optimize robust pipelines for data preparation ...

New

Astrion

Machine Learning Engineer

Huntsville, AL

$135K - $150K/yr

As needed Astrion seeking a Machine Learning Engineer to join our analytics team working on an innovative MLOps workload leveraging cutting-edge technologies and supporting a government customer in ...

Astrion

Machine Learning Engineer

Huntsville, AL · On-site

As needed Astrion seeking a Machine Learning Engineer to join our analytics team working on an innovative MLOps workload leveraging cutting-edge technologies and supporting a government customer in ...

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Mlops Machine Learning Engineer information

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$31.5K

$128.8K

$193.5K

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

As of Sep 7, 2026, the average yearly pay for mlops machine learning 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.

What does an MLOps machine learning engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

What are the key skills and qualifications needed to thrive as an MLOps machine learning engineer?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps machine learning engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

What is the difference between Mlops Machine Learning Engineer vs Data Scientist?

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

Are MLOps machine learning engineers in demand?

MLOps machine learning engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

Do MLOps Machine Learning Engineers need a degree?

MLOps Machine Learning Engineers typically do not require a formal degree but often have a background in computer science, data science, or related fields. Practical skills in machine learning, cloud platforms, and tools like Docker, Kubernetes, and CI/CD pipelines are highly valued. Certifications and hands-on experience can also enhance job prospects.
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Mlops Machine Learning Engineer jobs near you
Infographic showing various Mlops Machine Learning Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Engineer

Adidev Technologies Inc

Austin, TX

Full-time

Re-posted 25 days ago

Job description

Role: Jr-Mid Machine Learning Engineer

(This role is open to US Citizens, Green Card holders, GC-EAD only. We do not sponsor visas.)

Summary:

 Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced machine learning models, with a special emphasis on Generative AI. In this role, you will craft and refine AI-driven solutions, turning innovative ideas into value-adding features and services, thereby solidifying our market leadership and technological forefront for our clients.

About Adidev Technologies Inc.  

Adidev Technologies,(www.adidevtechnologies.com) is a premier IT consulting firm delivering top-notch, Machine Learning Engineer, iOS and Android, data scientist, Developer solutions to industry giants including Delta, Google, Apple, Spotify, US Bank, FedEx, and more. We're not just a software consulting company – we're a dynamic force shaping the future of technology. Partnering with industry giants, we consistently deliver groundbreaking solutions that redefine the digital landscape. As we continue to expand our footprint, we're on the hunt for exceptional individuals who can bring their technical prowess to our team and elevate our projects to new levels of innovation.

 

Expertise: We excel in IT consultative services and quality engineer development, with Good years of experience.

Global Presence: Our diverse employee workforce spans four continents.

Proven Track Record: Hundreds of Fortune 1000 and innovative startup clients with thousands of successful projects across the USA.

How We'll Guide You

Teaching and Development: We are dedicated to nurturing your growth and development, shaping you into an exceptional consultant capable of delivering top-tier solutions to our end clients.

Custom Support: An array of teams, from Development Managers to Tech Subject Matter Experts, are dedicated to your success.

Project Placement: A market-expertise team ensures you secure and thrive in projects with our esteemed clients.

Career Growth: We facilitate industry experience to propel your technical journey forward.

 

Key Responsibilities:

·        Architect and refine sophisticated ML models and algorithms, translating complex datasets into actionable solutions.

·        Engage in the full lifecycle of data modeling projects, from understanding business requirements to deployment and monitoring.

·        Execute comprehensive data analysis, including preprocessing, feature engineering, and leveraging Generative AI algorithms for novel solutions.

·        Lead cross-functional collaborations to integrate Generative AI models into our offerings, enhancing product capabilities and user experiences.

·        Apply advanced analytical techniques to analyze vast datasets, identifying trends, anomalies, and opportunities for improvement.

·        Execute data preprocessing, feature engineering, and algorithm optimization to enhance model accuracy and efficiency.

·        Conduct exploratory data analysis to extract valuable insights and influence strategic decisions.

·        Keep abreast of and implement the latest ML trends, tools, and best practices, including AutoML, MLOps, and interpretability frameworks.

·        Promote compliance with industry standards and regulatory requirements, emphasizing ethical AI practices.

 

Requirements:

·        Degree in Computer Science, Engineering, Statistics, or a related technical field.

·        Demonstrable experience in machine learning, deep learning, NLP, computer vision, reinforcement learning, and/or other AI domains.

·        Demonstrable experience with Generative AI models and frameworks, such as GANs or Transformers, applied in industry settings.

·        Practical experience with SQL/NoSQL databases, data visualization tools, and version control systems.

·        Strong foundational understanding of algorithmic complexity and data structure optimization.

·        Excellent problem-solving, collaboration, and communication abilities.

·        Develop and implement cutting-edge machine learning models, with a particular focus on Generative AI applications such as text generation, image synthesis, and creative AI.

·        Execute comprehensive data analysis, including preprocessing, feature engineering, and leveraging Generative AI algorithms for novel solutions.

·        Stay ahead of AI research, especially in Generative AI, applying the latest findings and techniques to drive innovation within our projects.

·        Proficiency in Python and ML libraries (TensorFlow, PyTorch, scikit-learn).

·        Strong background in cloud computing and big data platforms (AWS, Azure, GCP), with hands-on experience in cloud-based ML services and serverless architectures.

·        Familiarity with DevOps for AI, including containerization (Docker, Kubernetes), CI/CD pipelines, and MLOps practices.

·        Facilitate knowledge sharing and best practices in AI/ML, particularly focusing on Generative AI, within the team.

·        Ensure all AI implementations are compliant with ethical guidelines and data privacy standards.

How to Apply: 

Interested candidates are invited to submit a comprehensive application, including a latest updated resume and a detailed cover letter, showcasing your expertise.

Perks and Beyond! 

Competitive salary range: Based on experience and market value

Pack your bags! Paid relocation is on us.

Support, even from afar, with our remote assistance.

Regular salary reviews? You betcha!

Ready to Embark? 

 we invite you to take this extraordinary step with us. Showcase your journey in pushing the limits of mobile engineering by submitting your resume and a curated selection of your most influential projects.  At Adidev Technologies, we're dedicated to shaping your success. Join us to craft a future powered by innovation and growth.

Note: Adidev Technologies Inc. is a staunch advocate of diversity and equal opportunity. We warmly welcome applications from candidates of all backgrounds, experiences, and walks of life.  Your unique perspective could be the catalyst for our next revolutionary breakthrough

Employment Type: FULL_TIME

Apply