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Mlops Manager Jobs (NOW HIRING)

USM

JB061761 - MLOps Engineer

Grapevine, TX · On-site

$80/hr

MLOps Engineer Duration: 6 months+, possible extension Rate: $80/hr+, depending on experience ... management Data & Cloud Ecosystem Experience with: GCP (preferred), Azure, or hybrid environment ...

Entarian

MLOps Engineer

Arlington, VA

The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ...

DPR Construction

MLOps Engineer

Atlanta, GA · On-site

MLOps Engineer DPR is a leading construction company committed to delivering high-quality ... Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly ...

DPR Construction

MLOps Engineer

Raleigh, NC

MLOps Engineer DPR is a leading construction company committed to delivering high-quality ... Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly ...

DPR Construction

MLOps Engineer

Orlando, FL · On-site

... and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly ... MLOps practices, developing reusable patterns, documentation, and proof-of-concepts to drive ...

DPR Construction

MLOps Engineer

Tampa, FL

MLOps Engineer DPR is a leading construction company committed to delivering high-quality ... Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly ...

DPR Construction

MLOps Engineer

Fort Lauderdale, FL · On-site

MLOps Engineer DPR is a leading construction company committed to delivering high-quality ... Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly ...

DPR Construction

MLOps Engineer

Austin, TX · On-site

MLOps Engineer DPR is a leading construction company committed to delivering high-quality ... Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly ...

DPR Construction

MLOps Engineer

Dallas, TX

MLOps Engineer DPR is a leading construction company committed to delivering high-quality ... Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly ...

Wipro Limited

mlops Engineer

Richfield, PA · On-site

$60K - $135K/yr

... Release management Experience • 3-5 years of experience in MLOps, Machine Learning Engineering, or a related field Mandatory Skills: GCP AI ML MLOps. Experience: 5-8 Years. The expected ...

Cyber 1 Armor

Senior MLOps / LLMOps Engineer

Milpitas, CA · On-site

$119K - $163K/yr

Standardize MLOps and LLMOps workflows across teams Build and optimize CI/CD pipelines for ML and GenAI applications Deploy, monitor, and manage models in production environments Establish best ...

DPR Construction

MLOps Engineer

Baltimore, MD · On-site

MLOps Engineer DPR is a leading construction company committed to delivering high-quality ... Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly ...

Quince

Sr. Engineering Manager, MLOps

Palo Alto, CA · On-site

THE ROLE Senior Engineering Manager, MLOps We are seeking a Senior Engineering Manager, MLOps to join our growing team. The ideal candidate is a technical visionary with a proven track record of ...

Entarian

MLOps Engineer

Arlington, VA · On-site

The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ...

Entarian

MLOps Engineer

Arlington, VA · On-site

The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ...

Entarian

MLOps Engineer

Arlington, VA · On-site

The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ...

Entarian

MLOps Engineer

Arlington, VA · On-site

The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ...

Entarian

MLOps Engineer

Arlington, VA · On-site

The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ...

Apptronik

Staff MLOps Engineer

Austin, TX

This is a hands-on technical leadership role, not a management position; you will be a primary ... Own the technical direction for the MLOps platform - define subsystem interfaces, drive ...

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Mlops Manager information

What is the salary of MLOps manager?

The salary of an MLOps manager typically ranges from $110,000 to $160,000 annually, depending on experience, location, and company size. Senior roles or those in high-demand regions may offer higher compensation, often including benefits such as bonuses and stock options.

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?

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.

Is MLOps in high demand?

MLOps managers are in high demand due to the increasing adoption of machine learning and AI across industries. Organizations seek professionals skilled in deploying, monitoring, and maintaining ML models using tools like Kubernetes, Docker, and cloud platforms, making MLOps a rapidly growing field with strong job prospects.

What is an MLOps manager?

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 August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 12% Part Time, and 1% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution.

JB061761 - MLOps Engineer

USM

Grapevine, TX • On-site

$80/hr

Contractor

This job post has expired 2 days ago. Applications are no longer accepted.

Job description

  • Start Date: Interview Types
  • Skills . Experience owning .. Visa Types Green Card, US Citiz..

    • Client: Walmart Inc.
    Location: Grapevine, TX (Dallas, TX) - hybrid onsite
    Title: MLOps Engineer
    Duration: 6 months+, possible extension
    Rate: $80/hr+, depending on experience
    Description
    We are seeking a highly skilled MLOps Engineer to support the IRAS (Item Recognition as a Service) team, a core component of the ISEE (Intelligent Store Execution Engine) platform at Sam's Club.
    This role is responsible for owning and evolving the end-to-end MLOps lifecycle, enabling scalable, production-grade machine learning systems that power computer vision, RFID integration, and real-time item recognition across store environments.
    You will operate horizontally across multiple ML products and pipelines, ensuring reliability, scalability, and rapid iteration of ML-driven capabilities that support frictionless shopping experiences.
    Key Responsibilities
    MLOps Lifecycle Ownership
    Own the full ML lifecycle: data ingestion, model training, validation, deployment, monitoring, and retraining
    Build and maintain robust model pipelines for computer vision and IRAS-based item recognition system
    Implement data and model monitoring (drift detection, performance degradation, alerting)
    Refactor and productionize data science code into scalable, reusable service
    Platform & Pipeline Engineering
    Design and operate end-to-end ML pipelines (data → training → evaluation → deployment → feedback loops)
    Enable model versioning, reproducibility, and governance at scale
    Support real-time and batch inference systems tied to RFID + camera fusion pipelines [Sam's iSEE POC | PowerPoint]
    CI/CD & DevOps for ML
    Build and maintain CI/CD pipelines for ML workflows (model builds, testing, deployment)
    Automate testing, validation, and release processes for ML models and data pipeline
    Ensure high availability, rollback capability, and release governance
    Cross-Product / Horizontal Support
    Serve as a shared MLOps capability across multiple IRAS and ISEE initiative
    Partner with Data Scientists, CV/ML Engineers, and Platform teams to accelerate model delivery and adoption
    Standardize tools, frameworks, and best practices across team
    Required Skills & Experience
    Core Requirements (Must Have)
    Proven experience owning MLOps lifecycle end-to-end in production environment
    Strong Python engineering experience (building scalable services, pipelines)
    Hands-on expertise with CI/CD pipelines for ML system
    Experience supporting multiple ML products or platforms simultaneously
    MLOps & ML Tooling
    Deep knowledge of:
    MLflow / Kubeflow (or similar orchestration frameworks)
    Model versioning, experiment tracking, and pipeline orchestration
    Data monitoring, drift detection, and model observability
    Strong understanding of machine learning fundamentals and lifecycle management
    Data & Cloud Ecosystem
    Experience with:
    GCP (preferred), Azure, or hybrid environment
    Big Data ecosystems (Databricks, Spark, distributed processing)
    SQL and large-scale data pipeline development
    Familiarity with cloud-based ML infrastructure and scaling strategie
    Engineering & System
    Proficiency in:
    Shell scripting and automation
    Containerization and orchestration (Docker, Kubernetes)
    Building reliable, scalable backend systems for ML inference
    Preferred / Nice-to-Have
    Experience with computer vision pipelines (CV/ML models, object detection, item recognition)
    Exposure to RFID data integration or sensor fusion system
    Experience working in retail, edge + cloud hybrid environments, or real-time inference system
    Familiarity with GPU-based inference optimization and performance tuning
    What Success Looks Like
    Fully automated, production-grade ML pipelines supporting IRAS item recognition
    Reduced latency and improved reliability of model deployment and inference workflow
    Standardized MLOps practices across ISEE team
    High-confidence, monitored models with continuous improvement loop
    Top Skills Details
    Top Skills' Detail
    1. Experience owning MLOps lifecycle, from data monitoring to refactoring data science code to building robust ML model lifecycle.
    2. Python Engineering
    3. CI/CD
    4. Experience with MLOps driven data science outcomes and handle ML Engineering horizontal helping multiple products and initiatives.
    5. have strong knowledge of Machine Learning, MLOps, MLflow, Kubeflow, Python/R, SQL, Big Data, GCP, Shell scripting.
    Worksite Address
    1701 West State Highway 114,Grapevine,Texas,United States,76051
    Workplace Type
    Hybrid
    EVP
    You are getting to work with several teams that are on the cutting edge of technology for retail.
    Work Environment
    Fast paced, POC so like a startup, must be a self starter
    Additional Skills & Qualifications
    Must be W2. Prefer to have them in DFW area to go to the Grapevine Sam's Club 1-2 times per week but not an absolute must.
    Business Challenge
    By executing this IRAS project, we will be able to take on more of their monarch work going into next year. It will allow their item recognition service to exceed 85-90% accuracy

    Apply