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Mlops Machine Learning Engineer Jobs (NOW HIRING)

HeadHR

NY · On-site

$51.68 - $73.60/hr

... MLOps Engineer / Machine Learning Engineer lub w podobnej roli, * bardzo dobrze znasz Python i masz doświadczenie w budowie rozwiązań produkcyjnych, * posiadasz praktyczne doświadczenie z ...

innovitusa

Machine Learning Engineer

Atlanta, GA

W2 Candidates Only We are seeking a Machine Learning Engineer to develop, deploy, and optimize ... MLOps * Experience with AI/ML production environments #Hiring #W2 #MachineLearningEngineer ...

Constellation Space

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

The Role We are looking for a Machine Learning Engineer to bridge the gap between AI research and ... Build robust MLOps pipelines for continuous training and integration of models using telemetry data.

Constellation Space

Machine Learning Engineer

Seattle, WA · On-site

$95 - $135/hr

The Role We are looking for a Machine Learning Engineer to bridge the gap between AI research and ... Build robust MLOps pipelines for continuous training and integration of models using telemetry data.

1 point system

Machine Learning Engineer

Fort Mill, SC · Remote

$48/hr

Job Title Machine Learning Engineer Location Remote Rate $48/hr on W2 Must Haves: Neaural networks ... Microsoft Azure cloud platform * DevOps and/or MLOps practices * Model development, deployment ...

Errgo

NY · On-site

$120 - $160/hr

Python PyTorch TensorFlow AWS MLOps Spark About the role As a Machine Learning Engineer, the candidate will design, build, and deploy ML models that solve complex business problems at scale. This ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Qualifications: * 5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar role. * Proven experience deploying and maintaining machine learning models in production at scale.

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Qualifications: * 5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar role. * Proven experience deploying and maintaining machine learning models in production at scale.

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Qualifications: * 5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar role. * Proven experience deploying and maintaining machine learning models in production at scale.

UNAVAILABLE

Machine Learning Engineer

Frisco, TX · On-site

$140 - $190/hr

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 ...

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Mlops Machine Learning Engineer information

See salary details

$31.5K

$128.8K

$193.5K

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

As of Sep 6, 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.

MLOps/ Machine Learning Engineer

HeadHR

NY • On-site

$51.68 - $73.60/hr

Other

Posted 5 days ago

Job description

  • prowadzenie projektów MLOps end-to-end w branży bankowej – od analizy potrzeb biznesowych, przez projekt architektury, po wdrożenie i utrzymanie rozwiązań produkcyjnych,
  • projektowanie i implementacja rozwiązań opartych o Machine Learning oraz LLM zgodnie z najlepszymi praktykami MLOps / LLMOps,
  • rozwój i utrzymanie środowisk produkcyjnych w Kubernetes oraz Google Cloud Platform,
  • budowa i optymalizacja pipeline’ów MLOps (CI/CD, automatyzacja, monitoring modeli, governance),
  • integracja modeli ML/LLM z istniejącymi systemami i aplikacjami biznesowymi,
  • diagnozowanie problemów produkcyjnych oraz zapewnienie stabilności i niezawodności wdrożonych rozwiązań,
  • współpraca z zespołami Data Science, DevOps, Architektury oraz Security,
  • rekomendowanie nowych technologii i usprawnień w obszarze platformy ML/AI,
  • prowadzenie code review oraz mentoring członków zespołu,
  • dokumentowanie architektury oraz wdrożonych rozwiązań,
  • samodzielne podejmowanie decyzji technicznych i odpowiedzialność za ich realizację,
  • praca w środowisku Linux (Debian / RHEL),
  • praca hybrydowa – 1 x w tygodniu z biura w Warszawie,
  • stawka do 165 PLN/h + VAT (B2B).
Kogo poszukujemy?
  • masz doświadczenie w pracy jako MLOps Engineer / Machine Learning Engineer lub w podobnej roli,
  • bardzo dobrze znasz Python i masz doświadczenie w budowie rozwiązań produkcyjnych,
  • posiadasz praktyczne doświadczenie z Kubernetes,
  • pracowałeś/aś z chmurą (preferowana GCP),
  • rozumiesz architekturę rozwiązań Machine Learning oraz LLM i potrafisz je wdrażać w środowisku produkcyjnym,
  • znasz zagadnienia związane z MLOps / DevOps,
  • swobodnie poruszasz się w środowisku Linux (Debian / RHEL),
  • masz doświadczenie w samodzielnym prowadzeniu projektów technologicznych end-to-end,
  • potrafisz analizować problemy i proponować skuteczne rozwiązania,
  • dobrze odnajdujesz się we współpracy z biznesem i potrafisz przekładać wymagania na rozwiązania techniczne,
  • swobodnie komunikujesz się w języku angielskim.
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