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Manager Mlops Engineer Jobs in Addison, TX (NOW HIRING)

Prophecy Technologies

AI/ML Engineer

Plano, TX · On-site

$109K - $131K/yr

Build, automate, and maintain MLOps pipelines for model training, deployment, monitoring, and lifecycle management. * Collaborate with Data Scientists, Software Engineers, Data Engineers, and ...

MSR Cosmos

Google Cloud ML Engineer

Dallas, TX · On-site

$55.25 - $73.75/hr

... context management, slot filling, and rich fulfillment. * Demonstrated ability to leverage ... Solid understanding and practical application of MLOps best practices for chatbot pipelines ...

Paradigm

Senior ML Ops Engineer

Irving, TX · Remote

$123K - $170K/yr

What You Will Do: · Design, build, and maintain scalable MLOps solutions that support the end-to ... management. · Build and support containerized ML workloads and deployment workflows using ...

Ascentt

Senior Cloud Engineer

Plano, TX · On-site

$53.75 - $71.75/hr

Responsibilities : • Seeking a AWS Cloud Engineer to design, deploy, and manage cloud ... Experience in Databricks, Sagemaker, MLOps is essential. • Lead the design and implementation ...

Qorvo, Inc.

Data Engineer

Richardson, TX · On-site

$103K - $124K/yr

Help shape standards for model lifecycle management, MLOps, analytics engineering, and AI solution delivery. * Contribute to integration planning and enterprise analytics initiatives while following ...

Ascentt

Senior Cloud Engineer

Plano, TX · On-site

$53.25 - $71.25/hr

... manage cloud infrastructure on Cloud while supporting development teams with scalable solutions ... Experience in Databricks, Sagemaker, MLOps is essential. Key Duties and Tasks (If any specifics to ...

Johnson Controls

Ai/ML Engineer

Dallas, TX · On-site

$85K - $107K/yr

How you will do it ML Platform Engineering & MLOps (Azure-Focused) * Build and manage end-to-end ML/LLM pipelines on Azure ML using Azure DevOps for CI/CD, testing, and release automation.

Johnson Controls, Inc.

Ai/ML Engineer

Dallas, TX · On-site

$85K - $107K/yr

How you will do it ML Platform Engineering & MLOps (Azure-Focused) * Build and manage end-to-end ML/LLM pipelines on Azure ML using Azure DevOps for CI/CD, testing, and release automation.

Johnson Controls

Ai/ML Engineer

Dallas, TX · On-site

$85K - $107K/yr

How you will do it ML Platform Engineering & MLOps (Azure-Focused) * Build and manage end-to-end ML/LLM pipelines on Azure ML using Azure DevOps for CI/CD, testing, and release automation.

Delan Associates, Inc

AI Lead Engineer

Dallas, TX · On-site +1

$101K - $133K/yr

... MLOps CI/CD Pipelines Docker Kubernetes REST APIs & Microservices Cloud Platforms (Azure / AWS ... Retail domain experience Enterprise Transformation projects Model Governance Stakeholder Management ...

EssilorLuxottica

Data & ML Engineer

Dallas, TX · On-site

$113K - $136K/yr

  • Medical

  • Retirement

  • PTO

... Managing ML infrastructure, CI/CD, DevOps, and MLOps pipelines to support model training and deployment Managing platform performance, cost optimization, reliability, and availability Managing data ...

Essilor

Data & ML Engineer

Dallas, TX · On-site

$113K - $136K/yr

  • Medical

  • Retirement

  • PTO

... Managing ML infrastructure, CI/CD, DevOps, and MLOps pipelines to support model training and deployment Managing platform performance, cost optimization, reliability, and availability Managing data ...

EssilorLuxottica Group

Data & ML Engineer

Dallas, TX

$113K - $136K/yr

  • Medical

  • Retirement

  • PTO

... Managing ML infrastructure, CI/CD, DevOps, and MLOps pipelines to support model training and deployment Managing platform performance, cost optimization, reliability, and availability Managing data ...

Doist

AI Lead Engineer

Dallas, TX · On-site

$150 - $210/hr

Statistics & ML Algorithms * MLOps * CI/CD Pipelines * Docker * Kubernetes * REST APIs ... Stakeholder Management * Excellent Communication Skills #J-18808-Ljbffr

ConnectedX, Inc.

ML Engineer

Plano, TX · On-site

... with MLOps concepts, including model versioning, monitoring, and lifecycle management. · ... engineering best practices, including Git, testing, and CI/CD. · Strong analytical, problem ...

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Showing results 41-60

All JobsMlops Engineer JobsManager Mlops Engineer JobsManager Mlops Engineer Jobs in Addison, TX

Manager Mlops Engineer information

See Addison, TX salary details

$12

$54

$78

How much do manager mlops engineer jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for manager mlops engineer in Addison, TX is $54.20, according to ZipRecruiter salary data. Most workers in this role earn between $38.85 and $72.12 per hour, depending on experience, location, and employer.

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

AspectManager Mlops EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, Engineering, or related; experience with MLOps toolsDegree in Data Science, Statistics, or related; proficiency in programming and analytics
Work EnvironmentCollaborates with engineering and operations teams to deploy ML modelsAnalyzes data, builds models, and interprets results for business insights
Industry UsageUsed in tech, finance, healthcare for deploying ML solutionsCommon across tech, marketing, research for data analysis and modeling

The Manager Mlops Engineer focuses on deploying and maintaining machine learning models in production environments, overseeing MLOps pipelines. In contrast, Data Scientists primarily analyze data and develop models for insights. Both roles require technical skills but differ in their focus on deployment versus analysis.

What are popular job titles related to Manager Mlops Engineer jobs in Addison, TX?

For Manager Mlops Engineer jobs in Addison, TX, the most frequently searched job titles are:

What cities near Addison, TX are hiring for Manager Mlops Engineer jobs?

Cities near Addison, TX with the most Manager Mlops Engineer job openings:

Manager Mlops Engineer jobs near you
Infographic showing various Manager Mlops Engineer job openings in Addison, TX as of June 2026, with employment types broken down into 2% Internship, 49% Full Time, 8% Part Time, 38% Contract, and 3% Nights. Highlights an 77% Physical, 6% Hybrid, and 17% Remote job distribution, with an average salary of $112,743 per year, or $54.2 per hour.

AI/ML Engineer

Prophecy Technologies

Plano, TX • On-site

$109K - $131K/yr

Full-time

Posted 26 days ago

Job description


AI/ML Engineer
?? Location: Plano, TX (Hybrid)
?? Duration: Long-Term Contract
Client: EmergerTech - USLBM
Job Overview
We are seeking a highly skilled AI/ML Engineer with strong expertise in Machine Learning, Deep Learning, Generative AI, and Large Language Models (LLMs) to design, build, and deploy enterprise-scale AI solutions. The ideal candidate will have hands-on experience developing production-ready AI applications, implementing MLOps best practices, and building scalable cloud-based machine learning systems.
This role offers the opportunity to work on cutting-edge AI initiatives, including Generative AI, Retrieval-Augmented Generation (RAG), LLM fine-tuning, and intelligent enterprise applications.
Key Responsibilities
  • Design, develop, train, and deploy scalable Machine Learning and Deep Learning models for production environments.
  • Build AI-powered applications using traditional ML techniques, Generative AI, and Large Language Models (LLMs).
  • Develop and optimize data pipelines for structured and unstructured data processing.
  • Fine-tune foundation models and implement Retrieval-Augmented Generation (RAG) architectures.
  • Develop REST APIs and microservices using FastAPI, Flask, or similar frameworks to expose AI models.
  • Build, automate, and maintain MLOps pipelines for model training, deployment, monitoring, and lifecycle management.
  • Collaborate with Data Scientists, Software Engineers, Data Engineers, and business stakeholders to deliver AI-driven solutions.
  • Optimize model accuracy, scalability, inference performance, and latency.
  • Implement AI governance, responsible AI practices, model monitoring, and security best practices.
  • Stay current with emerging AI technologies, frameworks, and industry trends.

Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
  • 10+ years of hands-on experience in Artificial Intelligence, Machine Learning, or Data Science.
  • Strong programming experience with Python.
  • Experience with Machine Learning frameworks including TensorFlow, PyTorch, and Scikit-learn.
  • Hands-on experience with Large Language Models (LLMs), Prompt Engineering, and Generative AI.
  • Experience implementing Retrieval-Augmented Generation (RAG) solutions.
  • Knowledge of vector databases such as Pinecone, FAISS, Chroma, or Milvus.
  • Experience with MLOps platforms such as MLflow, Kubeflow, SageMaker, or Vertex AI.
  • Experience building REST APIs using FastAPI, Flask, or similar frameworks.
  • Strong understanding of SQL and NoSQL databases.
  • Hands-on experience with Docker, Kubernetes, Git, and CI/CD pipelines.
  • Experience working with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
  • Excellent analytical, communication, and problem-solving skills.

Preferred Qualifications
  • Experience with LangChain, LlamaIndex, or Semantic Kernel.
  • Experience working with Azure OpenAI, OpenAI APIs, Anthropic Claude, or Google Gemini.
  • Knowledge of distributed computing frameworks such as Apache Spark.
  • Experience with Databricks or Snowflake.
  • Familiarity with Responsible AI, AI Governance, and Model Monitoring.
  • AI/ML or Cloud certifications are a plus.

Technical Skills
  • Python
  • Machine Learning
  • Deep Learning
  • Generative AI
  • Large Language Models (LLMs)
  • Prompt Engineering
  • Retrieval-Augmented Generation (RAG)
  • LangChain / LlamaIndex
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • FastAPI / Flask
  • Docker
  • Kubernetes
  • MLflow / Kubeflow
  • SQL / NoSQL
  • Vector Databases (Pinecone, FAISS, Chroma, Milvus)
  • REST APIs
  • Git
  • CI/CD
  • AWS / Azure / Google Cloud Platform

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