ZipRecruiter

Log In

1

Senior Mlops Engineer Jobs in Silver Spring, MD (NOW HIRING)

Booz Allen Hamilton

Senior AI/ML Engineer

Alexandria, VA · On-site

$99K - $225K/yr

R0246859 AI/ML Engineer, Senior The Opportunity: As a Senior Artificial Intelligence and Machine ... You will contribute end-to-end, spanning data processing, model development, MLOps, and integration ...

Booz Allen Hamilton

AI/ML Engineer, Senior

Alexandria, VA · Hybrid

$99K - $225K/yr

AI/ML Engineer, Senior The Opportunity: As a Senior Artificial Intelligence and Machine Learning ... You will contribute endtoend, spanning data processing, model development, MLOps, and integration ...

Phase2 Technology

AI/ML Engineer, Senior

Alexandria, VA · On-site

$99 - $225/hr

R0246859 AI/ML Engineer, Senior The Opportunity As a Senior Artificial Intelligence and Machine ... You will contribute endtoend, spanning data processing, model development, MLOps, and integration ...

Via Logic LLC

Senior AI Engineer

Rockville, MD · On-site

$130 - $160/hr

As a Senior AI Engineer, you will * Support the development and operationalization of AI and ... LLMOps / MLOps * RAG architectures * AI orchestration frameworks * Kubernetes‑based AI ...

Humana

Senior Data Scientist

Washington, DC · Hybrid

We are seeking a Senior Data Scientist who will contribute to Generative AI initiatives at Humana ... MLOps & DevOps Collaboration Work with engineering and product teams to implement best practices ...

Humana

Senior Data Scientist

Washington, DC · Hybrid

We are seeking a Senior Data Scientist who will contribute to Generative AI initiatives at Humana ... MLOps & DevOps Collaboration Work with engineering and product teams to implement best practices ...

previous page

Showing results 41-60

All JobsMlops Engineer JobsSenior Mlops Engineer JobsSenior Mlops Engineer Jobs in Silver Spring, MD

Senior Mlops Engineer information

See Silver Spring, MD salary details

$61.5K

$130.8K

$189.7K

How much do senior mlops engineer jobs pay per year?

As of Sep 4, 2026, the average yearly pay for senior mlops engineer in Silver Spring, MD is $130,832.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,000.00 and $148,300.00 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.

What are the most commonly searched types of Mlops Engineer jobs in Silver Spring, MD?

The most popular types of Mlops Engineer jobs in Silver Spring, MD are:

What are popular job titles related to Senior Mlops Engineer jobs in Silver Spring, MD?

For Senior Mlops Engineer jobs in Silver Spring, MD, the most frequently searched job titles are:

What job categories do people searching Senior Mlops Engineer jobs in Silver Spring, MD look for?

The top searched job categories for Senior Mlops Engineer jobs in Silver Spring, MD are:

What cities near Silver Spring, MD are hiring for Senior Mlops Engineer jobs?

Cities near Silver Spring, MD with the most Senior Mlops Engineer job openings:

Senior Mlops Engineer jobs near you
Infographic showing various Senior Mlops Engineer job openings in Silver Spring, MD as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $130,832 per year, or $62.9 per hour.

Senior DevSecOps Engineer (ML Infrastructure)

Oslitandi Tech LLC

Washington, DC • On-site

$122K - $166K/yr

Full-time

Re-posted yesterday

Job description

Job Summary:
Oslitandi Tech LLC is a company that works with clients to achieve their tactical and strategic goals through sustainable technology solutions. The Senior DevSecOps Engineer will be responsible for designing and implementing a secure MLOps platform, ensuring compliance with DoD standards while utilizing Infrastructure as Code and container orchestration tools.
Responsibilities:
• Conceptualize, Design, Build, and Maintain a secure, automated, end-to-end MLOps pipeline leveraging tools like Kubeflow and MLflow for continuous model training, testing, and deployment.
• Create, manage, and support Infrastructure as Code (IaC) solutions utilizing Terraform and Ansible to reliably provision and manage complex platform deployments across varying DoD classification levels (IL5/IL6) and Cloud environments (AWS GovCloud/Azure).
• Implement, administer, and harden Kubernetes clusters (including networking, storage, and access controls) to strictly meet DoD STIGs and compliance standards (e.g., NIST 800-53, RMF).
• Integrate continuous security scanning tools (SAST/DAST) and vulnerability management directly into the GitLab CI/CD workflow to ensure a DevSecOps posture and enable automated DoD Iron Bank compliance.
• Deploy and manage service mesh technologies, such as Istio or Linkerd, to enforce mTLS, traffic management, and policy enforcement across containerized microservices.
• Develop, manage, and support automation solutions for infrastructure and application orchestration using scripting languages such as Python or Go.
Qualifications:
Required:
• A minimum of 5+ years of experience in DevOps, Cloud/Platform Engineering, or Site Reliability Engineering (SRE).
• At least 3+ years of direct, hands-on experience administering and deploying applications on Kubernetes.
• Expert-level proficiency in defining, deploying, and managing infrastructure using Terraform.
• Proficiency in scripting and development skills (Python or Go) for automation tasks and tooling.
• Experience with configuring and managing CI/CD pipelines, specifically GitLab CI/CD and container registries.
• Working knowledge of security controls, compliance standards, and hardening practices (STIGs, RMF, NIST).
• The candidate shall have a Bachelor's degree in Computer Science, Engineering, or a related technical field.
• Must possess active DoD 8570 IAT Level II certification (Security+ or equivalent) REQUIRED.
• Must be eligible for a U.S. Government Secret / TS Clearance.
Preferred:
• CKA (Certified Kubernetes Administrator) or AWS Certified Solutions Architect certification preferred.
Company:
Our company works with clients to achieve their tactical and strategic goals by unifying sustainable technology solutions which reduce costs, decrease cycle times, and seamlessly manage processes throughout the enterprise. Founded in , the company is headquartered in Washington, USA, with a team of 2-10 employees. The company is currently Early Stage.

Apply