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Mlops Engineer Salary Jobs (NOW HIRING)

Jobgether

Our partner is looking for a MLOps Engineer based in Netherlands. Join a high-impact engineering ... Competitive salary and equity package. * Comprehensive healthcare coverage for employees and ...

Stefanini

MLOps Engineer

Dearborn, MI · On-site

Stefanini is looking for a MLOps Engineer (Dearborn, MI) For quick apply, please reach out to ... Listed salary ranges may vary based on experience, qualifications, and local market. Also, some ...

Booz Allen Hamilton

MLOps Engineer, Mid

Chantilly, VA

$77K - $176K/yr

MLOps Engineer, Mid The Opportunity : Are you looking for an opportunity to make a difference and ... Salary at Booz Allen is determined by various factors, including but not limited to location, the ...

Booz Allen Hamilton

MLOps Engineer, Mid

Alexandria, VA · On-site

$77K - $176K/yr

MLOps Engineer, Mid The Opportunity : Are you looking for an opportunity to make a difference and ... Salary at Booz Allen is determined by various factors, including but not limited to location, the ...

Booz Allen Hamilton

MLOps Engineer, Mid

Aurora, CO · On-site

$77K - $176K/yr

MLOps Engineer, Mid The Opportunity : Are you looking for an opportunity to make a difference and ... Salary at Booz Allen is determined by various factors, including but not limited to location, the ...

Booz Allen Hamilton

Mid MLOps Engineer

Chantilly, VA · On-site

$77K - $176K/yr

R0241240 MLOps Engineer, Mid The Opportunity : Are you looking for an opportunity to make a ... Salary at Booz Allen is determined by various factors, including but not limited to location, the ...

Booz Allen Hamilton, Inc.

MLOps Engineer, Mid

Chantilly, VA · On-site

$77K - $176K/yr

MLOps Engineer, Mid The Opportunity : Are you looking for an opportunity to make a difference and ... Salary at Booz Allen is determined by various factors, including but not limited to location, the ...

C the Signs

Senior MLOps Engineer

$107K - $146K/yr

Position Summary We're hiring a Senior MLOps Engineer with deep machine learning engineering ... Competitive salary and benefits package. * Flexible working arrangements (remote or hybrid options ...

NBCUniversal

Staff MLOps Engineer

Manhattan, NY

We are seeking a Staff MLOps Engineer with experience building and scaling infrastructure for large ... Salary range: $220,000k - 260,000 + 10% (bonus eligibility). Additional Information As part of our ...

ClimateAi

Senior MLOps Engineer

San Francisco, CA

$170K - $200K/yr

The Role As a Senior MLOps Engineer, you will own the infrastructure and ML platform that powers ... This salary range may be inclusive of several career levels at ClimateAi and will be narrowed ...

Nace AI

Senior MLOps Engineer

Palo Alto, CA · On-site

$122K - $168K/yr

As a Senior MLOps Engineer, you will own the infrastructure that takes Nace.AI's models from ... Silicon Valley-standard salary, significant equity, and premium benefits.

NBCUniversal

Staff MLOps Engineer

Manhattan, NY

We are seeking a Staff MLOps Engineer with experience building and scaling infrastructure for large ... Salary range: $220,000k - 260,000 + 10% (bonus eligibility). Additional Information As part of our ...

NBCUniversal

Staff MLOps Engineer

Manhattan, NY

We are seeking a Staff MLOps Engineer with experience building and scaling infrastructure for large ... Salary range: $220,000k - 260,000 + 10% (bonus eligibility). Additional Information As part of our ...

ClimateAi

Senior MLOps Engineer

San Francisco, CA · On-site

$170K - $200K/yr

The Role As a Senior MLOps Engineer, you will own the infrastructure and ML platform that powers ... This salary range may be inclusive of several career levels at ClimateAi and will be narrowed ...

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All JobsMlops Engineer Salary Jobs

Mlops Engineer Salary information

See salary details

$38K

$115.9K

$191.5K

How much do mlops engineer salary jobs pay per year?

As of Jul 26, 2026, the average yearly pay for mlops engineer salary in the United States is $115,864.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,000.00 and $151,500.00 per year, depending on experience, location, and employer.

Are MLOps engineers in demand?

Yes, MLOps engineers are in high demand due to the increasing adoption of machine learning and AI 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.

What engineer makes $500,000 a year?

A senior or lead MLOps engineer with extensive experience, specialized skills in cloud platforms, automation, and deployment pipelines can earn $500,000 or more annually, especially in high-cost-of-living areas or within large tech companies. Such roles often require advanced certifications, strong programming skills, and a deep understanding of machine learning infrastructure and operations.

What engineers make $300,000 a year?

Senior MLOps engineers with extensive experience, specialized skills in cloud platforms, automation, and large-scale deployment can earn $300,000 or more annually. High compensation often reflects expertise in machine learning pipelines, infrastructure, and advanced tools like Kubernetes and TensorFlow, especially in competitive tech environments.

What engineers make $200,000 a year?

Senior MLOps engineers with extensive experience, advanced skills in cloud platforms, automation, and machine learning deployment can earn $200,000 or more annually. High salaries are often associated with large tech companies, specialized expertise, and leadership roles in AI and data infrastructure.

What is the difference between Mlops Engineer Salary vs Data Scientist Salary?

AspectMlops Engineer SalaryData Scientist Salary
Average Annual Salary$110,000 - $150,000$95,000 - $135,000
Required SkillsMachine Learning, DevOps, Cloud ComputingStatistics, Programming, Data Analysis
Work EnvironmentTech companies, AI startups, cloud providersResearch institutions, tech firms, finance
CertificationsCloud certifications, ML certificationsData Science certifications, Python/R skills

Generally, Mlops Engineers tend to have higher salaries due to their specialized skills in deploying and maintaining machine learning models in production environments. Data Scientists focus more on data analysis and model development. Both roles are in high demand, but Mlops Engineers often command a premium because of their expertise in operationalizing AI solutions.

More about Mlops Engineer Salary jobs
What cities are hiring for Mlops Engineer Salary jobs? Cities with the most Mlops Engineer Salary job openings:
What states have the most Mlops Engineer Salary jobs? States with the most job openings for Mlops Engineer Salary jobs include:
What job categories do people searching Mlops Engineer Salary jobs look for? The top searched job categories for Mlops Engineer Salary jobs are:
Mlops Engineer Salary jobs near you
Infographic showing various Mlops Engineer Salary job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $115,864 per year, or $55.7 per hour.

MLOps Engineer

Jobgether

On-site, Remote

Full-time

Medical

Posted 5 days ago

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a MLOps Engineer based in Netherlands.

Join a high-impact engineering team building the infrastructure that powers next-generation AI solutions for enterprise-scale decision-making. In this role, you will design, deploy, and optimize production-grade machine learning systems that support the full ML lifecycle, from training to inference. You'll collaborate with talented engineers to create highly scalable, reliable, and secure MLOps platforms capable of handling demanding workloads. This is an opportunity to solve complex technical challenges, improve model performance at scale, and contribute to cutting-edge AI technologies in a fast-paced, collaborative, and remote-first environment. The role offers significant ownership, modern cloud-native tooling, and the chance to shape the future of production AI systems.

Accountabilities
  • Develop, automate, and maintain scalable machine learning pipelines, CI/CD workflows, and orchestration frameworks to support efficient model development and deployment.
  • Design and implement high-performance model serving infrastructure using industry-standard serving frameworks while optimizing inference for low latency and high throughput.
  • Build reliable deployment strategies including A/B testing, canary releases, rollback mechanisms, and production validation processes.
  • Create robust monitoring, logging, alerting, and observability solutions to ensure model reliability, performance, and operational excellence.
  • Optimize infrastructure utilization by improving GPU efficiency, enabling autoscaling, and managing cloud resources effectively.
  • Design and maintain feature stores, scalable data pipelines, and storage architectures capable of supporting large-scale training and inference workloads.
  • Collaborate with engineering teams to continuously improve platform scalability, security, governance, and operational best practices.
Requirements
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline, or equivalent practical experience.
  • At least 5 years of experience in MLOps, DevOps, or related engineering roles supporting production machine learning environments.
  • Proven experience designing and building MLOps infrastructure from the ground up using platforms such as MLflow, Weights & Biases, Kubeflow, or similar.
  • Strong hands-on experience with machine learning frameworks including PyTorch and TensorFlow, as well as model serving technologies such as TorchServe, TensorFlow Serving, Triton, or KServe.
  • Solid experience developing and managing scalable data pipelines, Kubernetes environments, cloud infrastructure (AWS, GCP, or Azure), and Infrastructure as Code solutions including Terraform, Helm, or GitOps.
  • Strong programming skills in Python, Bash, and Go, with a focus on maintainable, scalable, and production-quality software.
  • Knowledge of AI system security, model governance, compliance, monitoring, and observability tools such as Prometheus, Grafana, Datadog, or OpenTelemetry.
  • Experience with FastAPI, Databricks, Snowflake, SRE practices, or cloud security certifications is considered an advantage.
Benefits
  • Competitive salary and equity package.
  • Comprehensive healthcare coverage for employees and eligible dependents.
  • Paid parental leave supporting all paths to parenthood, including adoption and surrogacy.
  • Relocation assistance for employees joining one of the company's office locations where applicable.
  • Fully remote work within Europe.
  • Opportunity to work on cutting-edge AI technologies with significant technical ownership.
  • Inclusive, collaborative, and mission-driven engineering culture focused on innovation, learning, and professional growth.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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