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Senior Mlops Engineer Jobs (NOW HIRING)

AppRecode, Inc.

NY · On-site

$120 - $160/hr

They need a senior MLOps engineer to build end‑to‑end ML pipelines in the cloud, automate model training and deployment, and ensure production ML systems are monitored, reliable, and scalable.

NVIDIA Corporation

Senior MLOps Engineer

Santa Clara, CA · On-site

$184 - $357/hr

NVIDIA is seeking a Senior MLOps Engineer to join our Autonomous Driving organization in Santa Clara, CA. This individual contributor will design and operate end‐to‐end data and ML pipelines for ...

NVIDIA Corporation

$184 - $357/hr

NVIDIA is seeking a Senior MLOps Engineer to join our Autonomous Driving organization in Santa Clara, CA. This individual contributor will design and operate end‐to‐end data and ML pipelines for ...

New

Nvidia Corporation

Senior MLOps Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

NVIDIA is seeking a Senior MLOps Engineer to join our Autonomous Driving organization in Santa Clara, CA. This individual contributor will design and operate end-to-end data and ML pipelines for ...

Analytica

Senior MLOps Engineer

Washington, DC · On-site

$118K - $162K/yr

  • Medical

  • Retirement

Analytica is seeking a highly skilled Senior MLOps Engineer to lead the design, development, and deployment of machine learning operations infrastructure for defense applications. This role requires ...

Nvidia

Senior MLOps Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

NVIDIA is seeking a Senior MLOps Engineer to join our Autonomous Driving organization in Santa Clara, CA. This individual contributor will design and operate endtoend data and ML pipelines for NVIDIA ...

Nace.AI

Senior MLOps Engineer

Palo Alto, CA · On-site

$210 - $280/hr

As a Senior MLOps Engineer, you will own the infrastructure that takes Nace.AI's models from research to reliable, production‑grade systems. Our infrastructure generates task‑specific Small ...

Oura

Senior MLOps Engineer

$107K - $146K/yr

  • Medical

  • Dental

  • Vision

  • PTO

We are looking for a Senior MLOps Engineer to join our Data Engineering & Analytics team. In this role, your primary focus will be leading the design and evolution of the platforms, workflows, and ...

C the Signs

Senior MLOps Engineer

$107K - $146K/yr

Position Summary We're hiring a Senior MLOps Engineer with deep machine learning engineering experience to build and operate the production platform powering ML/LLM-driven healthcare workflows. You ...

Ōura

Senior MLOps Engineer

$107K - $146K/yr

  • Medical

  • Dental

  • Vision

  • PTO

We are looking for a Senior MLOps Engineer to join our Data Engineering & Analytics team. In this role, your primary focus will be leading the design and evolution of the platforms, workflows, and ...

Analytica

Senior MLOps Engineer

Washington, DC · On-site

$117K - $161K/yr

  • Medical

  • Retirement

Analytica is seeking a highly skilled Senior MLOps Engineer to lead the design, development, and deployment of machine learning operations infrastructure for defense applications. This role requires ...

Nace AI

Senior MLOps Engineer

Palo Alto, CA · On-site

$180 - $240/hr

Role Overview As a Senior MLOps Engineer, you will own the infrastructure that takes Nace.AI's models from research to reliable, production-grade systems. Our infrastructure generates task‑specific ...

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 research to reliable, production-grade systems. Our infrastructure generates task-specific Small Language ...

KOHLS

Senior MLOps Engineer (Remote)

Menomonee Falls, WI · On-site

$104K - $144K/yr

About the Role As Senior MLOps Engineer, you will focus on supporting cross-functional teams in designing, deploying, and operating machine learning solutions while building scalable infrastructure ...

Kohl's

$95K - $131K/yr

Role Specific Information About the Role As Senior MLOps Engineer, you will focus on supporting cross-functional teams in designing, deploying, and operating machine learning solutions while building ...

Zeitview (formerly DroneBase)

Senior MLOps Engineer I

Boston, MA · On-site

$170 - $180/hr

  • Medical

  • Dental

  • Vision

  • PTO

About the Role As the Senior MLOps Engineer I, you will help turn the models built by our ML Scientists, Data Scientists, and Perception Engineers into reliable, production‑grade services. You will ...

Zeitview

Senior MLOps Engineer I

San Francisco, CA · On-site +1

$123K - $169K/yr

  • Medical

  • Dental

  • Vision

  • PTO

As the Senior MLOps Engineer I, you will help turn the models built by our ML Scientists, Data Scientists, and Perception Engineers into reliable, production-grade services. You'll work on the ...

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Senior Mlops Engineer information

See salary details

$59.5K

$126.6K

$183.5K

How much do senior mlops engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for senior mlops engineer in the United States is $126,557.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,500.00 and $143,500.00 per year, depending on experience, location, and employer.

What is a senior MLOps engineer?

A Senior MLOps Engineer is an experienced professional who bridges the gap between data science, machine learning, and software engineering. They are responsible for designing, deploying, and maintaining scalable machine learning systems in production environments. Their role involves automating workflows, monitoring model performance, ensuring reproducibility, and managing the infrastructure needed to support machine learning operations. Senior MLOps Engineers also collaborate with data scientists, software developers, and IT teams to ensure smooth integration and continuous delivery of ML models. They play a crucial role in making machine learning solutions reliable, efficient, and scalable for business applications.

What are the key skills and qualifications needed to thrive as a senior MLOps engineer?

To thrive as a Senior MLOps Engineer, you need deep expertise in machine learning workflows, software engineering, and cloud infrastructure, typically supported by a degree in computer science or related fields. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, and platforms such as AWS, GCP, or Azure, as well as certifications in cloud or DevOps, are highly valuable. Strong problem-solving, collaboration, and communication skills set standout professionals apart in this role. These skills and qualities are crucial to ensuring robust, scalable, and efficient deployment of machine learning models in production environments.

What are some common challenges senior MLOps engineers face when deploying machine learning models to production environments?

Senior MLOps Engineers often encounter challenges such as managing model versioning, ensuring reproducibility, and scaling deployments across diverse infrastructure. Balancing the needs of data scientists for experimentation with the stability and reliability requirements of production systems can be complex. Additionally, integrating continuous integration and continuous deployment (CI/CD) pipelines for ML workflows and monitoring model performance post-deployment are ongoing responsibilities. Collaboration with data scientists, software engineers, and IT operations is crucial to address these challenges and maintain robust, efficient ML systems.

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

AspectSenior Mlops EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, Engineering, or related; experience with ML deployment toolsBachelor's/Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in productionFocus on data analysis, model development, and insights generation
Industry UsageUsed in tech, finance, healthcare for ML deploymentUsed across industries for data analysis and modeling

The main difference is that Senior Mlops Engineers specialize in deploying and maintaining machine learning models in production environments, while Data Scientists focus on developing models and analyzing data. Both roles require strong technical skills, but their day-to-day tasks and focus areas differ significantly.

Are senior MLOps engineers in demand?

Senior MLOps engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are valued for their expertise in deploying, managing, and scaling machine learning models using tools like Kubernetes, Docker, and cloud platforms. The role often requires strong skills in automation, CI/CD pipelines, and cloud infrastructure, making experienced professionals highly sought after.

How much do senior MLOps engineers make?

Senior MLOps engineers typically earn between $120,000 and $180,000 annually, depending on experience, location, and company size. They often have expertise in cloud platforms, automation tools, and machine learning deployment pipelines, which can influence salary levels.
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Senior Mlops Engineer jobs near you
Infographic showing various Senior Mlops Engineer job openings in the United States as of August 2026, with employment types broken down into 94% Full Time, 2% Part Time, and 4% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $126,557 per year, or $60.8 per hour.

Senior MLOps Engineer

AppRecode, Inc.

NY • On-site

$120 - $160/hr

Other

Posted 14 days ago

Job description

About the Position

The client is focused on improving and scaling machine learning systems. They need a senior MLOps engineer to build end‑to‑end ML pipelines in the cloud, automate model training and deployment, and ensure production ML systems are monitored, reliable, and scalable.

Start: December 1, 2025

Key Responsibilities
  • Automate machine learning model training and deployment processes using CI/CD pipelines
  • Build end-to-end MLOps pipelines in cloud platforms (AWS / GCP / Azure)
  • Implement monitoring and observability for ML models in production environments
  • Optimize infrastructure for ML workloads to improve reliability, scalability, and efficiency
  • Deploy and manage containerized ML applications using Docker and Kubernetes
  • Implement model versioning, experiment tracking, and model registry solutions
  • Set up data pipelines and feature stores for ML model training
  • Ensure ML model performance monitoring, drift detection, and retraining automation
  • Collaborate with data scientists to operationalize ML models from development to production
  • Implement infrastructure as code for ML infrastructure using Terraform or similar tools

Reports to: Client’s Engineering Manager / CTO

Collaborates with: Data Science team, Engineering teams, DevOps team

Technologies

Must-have: MLOps practices, CI/CD for ML (GitHub Actions, GitLab CI, Azure DevOps), Docker, Kubernetes, Cloud platforms (AWS / GCP / Azure), Python, Infrastructure as Code (Terraform), ML frameworks (TensorFlow, PyTorch, scikit-learn), Model deployment (SageMaker, Vertex AI, Azure ML, or Kubeflow)

Nice-to-have: MLflow, Weights & Biases, DVC, Feature stores (Feast, Tecton), Model monitoring (Evidently, WhyLabs), Apache Airflow, Spark, Ray, Helm, ArgoCD, Prometheus, Grafana, Data versioning, A/B testing for models

Soft Skills
  • Fluent English (conversational and written)
  • Strong problem-solving and analytical skills
  • Ability to work independently and implement ML processes end-to-end
  • Collaboration skills working with data scientists and engineers
  • Understanding of ML model lifecycle from data to production
  • Highly self‑managed and able to plan, estimate, and execute tasks
Challenges & Milestones

First 90 Days: Assess current ML infrastructure, implement initial MLOps automation, set up model monitoring for production models

Months 3-6: Build end-to-end ML pipelines with automated training and deployment, implement experiment tracking and model registry, optimize infrastructure costs

Months 6-12: Full MLOps platform operational with automated retraining, drift detection, A/B testing capabilities, and scalable infrastructure supporting multiple ML models

Working Hours

Full-time (40 hours/week), Remote

Flexible hours with reasonable overlap for team collaboration

We are seeking a Senior MLOps Engineer to build and scale machine learning systems in the cloud. This role focuses on automating ML model training, deployment, and monitoring to ensure reliable production ML operations.

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