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Mlops Manager Jobs (NOW HIRING)

Tech Tammina LLC

MLOps Platform Engineer

Reston, VA · On-site

MLOps Platform Engineer Location: Reston VA Required Qualifications · 3+ years of hands-on ... managing CI/CD pipelines (GitLab or equivalent). · Familiarity with machine learning workflows ...

Kapitus

MLOps Architect - Gen Al

Washington, DC

MLOps & GenAI Platform Architecture * Design and implement scalable ML and LLM infrastructure on ... Managed services (e.g., SageMaker endpoints, Bedrock-style APIs) * Containerized custom inference ...

ITCAPS LLC

Senior MLOps / LLMOps Engineer

Jersey City, NJ

$109K - $149K/yr

Job Title - Senior MLOps / LLMOps Engineer Kubernetes & AI Inference Platforms Duration - 2 Months ... Deploy, manage, and troubleshoot containerized AI/LLM applications on Kubernetes/OpenShift ...

Kapitus

MLOps Architect - Gen Al

Arlington, VA · On-site

We are seeking a senior MLOps Architect to design and scale a modern ML and Generative AI platform ... Managed services (e.g., SageMaker endpoints, Bedrock-style APIs) * Containerized custom inference ...

Tech Tammina

MLOps Platform Engineer

Reston, VA · On-site

MLOps Platform Engineer Location: Reston VA Required Qualifications • 3+ years of hands-on ... Preferred Qualifications • Experience managing Data Analytics Platforms / Tools (e.g., Domino ...

Apple

Machine Learning (MLOps) Engineer

Cupertino, CA · On-site

As an MLOps Engineer, you will be the backbone of our machine learning infrastructure, ensuring ... Experience building and managing CI/CD pipelines for ML workflows using tools such as Jenkins ...

Booz Allen Hamilton

MLOps Engineer, Mid

Chantilly, VA · On-site

$77K - $176K/yr

Experience with leveraging MLOps platforms and Machine Learning (ML) CI/CD workflows to manage datasets and model training, deployment, and monitoring * Knowledge of the ML lifecycle and concepts to ...

Kapitus

MLOps Architect - Gen Al

Arlington, VA · On-site

MLOps & GenAI Platform Architecture * Design and implement scalable ML and LLM infrastructure on ... Managed services (e.g., SageMaker endpoints, Bedrock-style APIs) * Containerized custom inference ...

smart folks inc

MLOps Developer

Sunnyvale, CA · On-site

MLOPS Ray Developer Location: Austin, TX/ Sunnyvale, CA/ Remote Duration: Long-term * Deep ... Interact with and support partner teams, including Engineering, QA, and program management.

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Mlops Manager information

What is the difference between Mlops Manager vs Data Scientist?

AspectMlops ManagerData Scientist
Required CredentialsBachelor's/Master's in CS, Engineering, or related; certifications in cloud platforms or MLOps toolsBachelor's/Master's in CS, Statistics, or related; certifications in data analysis or machine learning
Work EnvironmentCollaborates with engineering, DevOps, and data teams to deploy and maintain ML systemsAnalyzes data, builds models, and provides insights to inform business decisions
Employer & Industry UsageTech companies, AI startups, enterprises implementing ML pipelinesResearch institutions, tech firms, finance, healthcare, and marketing sectors

The Mlops Manager focuses on deploying, maintaining, and optimizing machine learning systems within an organization, working closely with engineering and DevOps teams. In contrast, a Data Scientist primarily analyzes data, develops models, and provides insights. While both roles require knowledge of machine learning, the Mlops Manager emphasizes operationalizing ML solutions, whereas the Data Scientist emphasizes data analysis and modeling.

What are the key skills and qualifications needed to thrive as an MLOps Manager, and why are they important?

To thrive as an MLOps Manager, you need expertise in machine learning, software engineering, and DevOps practices, often backed by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, Azure, GCP), and certifications such as AWS Certified Machine Learning or Google Cloud Professional ML Engineer are highly beneficial. Strong leadership, problem-solving, and cross-functional communication skills help manage teams and bridge the gap between data science and IT operations. These abilities are crucial for ensuring reliable, scalable, and efficient deployment of machine learning solutions in production environments.

What are some common challenges an MLOps Manager faces when integrating machine learning models into production environments?

MLOps Managers often encounter challenges such as ensuring seamless collaboration between data science and engineering teams, managing model versioning, and maintaining reliable deployment pipelines. Balancing rapid experimentation with the need for robust, scalable, and secure production systems can be complex. Additionally, monitoring model performance post-deployment and handling data drift or model degradation are ongoing responsibilities. Effective communication and establishing standardized processes are key to overcoming these challenges and ensuring successful model operations.

What are MLOps Managers?

MLOps Managers are professionals responsible for overseeing the deployment, operation, and scaling of machine learning models in production environments. They coordinate teams to ensure seamless collaboration between data scientists, engineers, and IT staff, facilitating the automation of machine learning workflows. Their role involves managing infrastructure, optimizing processes for model monitoring and maintenance, and ensuring compliance with organizational and industry standards. MLOps Managers play a key role in bridging the gap between model development and operationalization, ensuring that machine learning solutions are reliable, reproducible, and scalable.
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Mlops Manager jobs near you
Infographic showing various Mlops Manager job openings in the United States as of May 2026, with employment types broken down into 2% Full Time, 89% Part Time, 2% Temporary, 6% Contract, and 1% Nights. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution.

MLOps Platform Engineer

Tech Tammina LLC

Reston, VA • On-site

Contractor

Posted 5 days ago

Job description

Job title: MLOps Platform Engineer

Location: Reston VA
 

Required Qualifications

· 3+ years of hands-on experience with AWS services, including EKS, EC2, S3, IAM, CloudWatch, and ECR.

· Strong experience operating and troubleshooting Kubernetes (preferably AWS EKS).

· Proficiency in containerization (Docker) and orchestration concepts.

· Strong programming/scripting experience in Python and Bash.

· Experience building and managing CI/CD pipelines (GitLab or equivalent).

· Familiarity with machine learning workflows, including training, inference, and model monitoring.

· Experience with infrastructure-as-code (Terraform or CloudFormation).

· Experience supporting production platforms, including incident management and root cause analysis.

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Preferred Qualifications

· Experience managing Data Analytics Platforms / Tools (e.g., Domino, SageMaker)

· Experience with ML lifecycle tools such as MLflow, or similar.

· Experience supporting GPU-based workloads or distributed training environments.

· Familiarity with enterprise MLOps architectures and patterns (batch, real-time, microservices).

· Understanding of data processing frameworks and feature pipelines.

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Other Competencies

· Strong analytical, troubleshooting, and problem-solving skills.

· Effective communication and documentation abilities.

· Ability to collaborate across engineering, analytics, and product teams.

· Self-motivated with the ability to drive initiatives independently.

· Ability to work in a complex, regulated enterprise environment