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Mlops Jobs in Texas (NOW HIRING)

Conch Technologies Inc

MLOps Engineer

Dallas, TX · On-site

MLOps Engineer Location: Grapevine, TX & Dallas, TX - (Hybrid) Duration: 6+ Months Contract Key Responsibilities MLOps Lifecycle Ownership Own the full ML lifecycle: data ingestion, model training ...

USM

JB061761 - MLOps Engineer

Grapevine, TX · On-site

$80/hr

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 ...

Lorven Technologies

MLOps Engineer

Austin, TX · On-site

Our client is looking MLOps Engineer project Austin, TX (Onsite) below is the detailed requirements. Job Title : MLOps Engineer Location : Austin, TX (Onsite) Duration : Long term * Bachelor's degree ...

Apptronik

Staff MLOps Engineer

Austin, TX · On-site

JOB SUMMARY Apptronik is seeking a Staff MLOps Engineer to own the technical direction of our MLOps platform - the system of record for datasets, experiments, model artifacts, and serving paths that ...

Apptronik

Staff MLOps Engineer

Austin, TX · On-site

JOB SUMMARY Apptronik is seeking a Staff MLOps Engineer to own the technical direction of our MLOps platform - the system of record for datasets, experiments, model artifacts, and serving paths that ...

KAPI LLC

Be Seen First

Senior MLOps Engineer - Snowflake

Dallas, TX · On-site

$100K - $130K/yr

Job Summary We are seeking a highly experienced Senior MLOps Engineer with strong hands-on Snowflake experience to support enterprise machine learning platforms and production ML workloads. The ideal ...

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See Texas salary details

$89.3K

$140.1K

$166.7K

How much do mlops jobs pay per year?

As of Sep 1, 2026, the average yearly pay for mlops in Texas is $140,082.00, according to ZipRecruiter salary data. Most workers in this role earn between $132,354.00 and $152,141.00 per year, depending on experience, location, and employer.

What is MLOps?

MLOps, short for Machine Learning Operations, is a set of practices that combines machine learning, DevOps, and data engineering to automate and streamline the deployment, monitoring, and maintenance of machine learning models in production. MLOps aims to improve collaboration between data scientists and operations teams, ensuring that models are robust, scalable, and easily updated. It covers the entire machine learning lifecycle, from data preparation to model training, deployment, and ongoing monitoring. By implementing MLOps, organizations can accelerate the development and deployment of reliable machine learning solutions.

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

To thrive as an MLOps Engineer, you need a strong background in machine learning, software engineering, and DevOps principles, often supported by a degree in computer science or a related field. Proficiency with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (e.g., AWS, Azure, GCP), and ML frameworks is typically required, along with certifications in cloud or DevOps technologies. Strong problem-solving skills, collaboration, and communication abilities help MLOps professionals excel in cross-functional teams and manage complex workflows. These skills are vital for reliably deploying, monitoring, and scaling machine learning models in production environments, ensuring efficiency and robustness.

What are some common challenges faced by MLOps professionals when deploying machine learning models to production?

MLOps professionals often encounter challenges such as ensuring reproducibility of models, managing version control for both code and data, and maintaining model performance over time. Handling continuous integration and deployment (CI/CD) pipelines for ML models can be complex, especially when dealing with large datasets and evolving algorithms. Additionally, coordinating with data scientists, software engineers, and DevOps teams to streamline workflows and monitor models post-deployment are key responsibilities that require both technical expertise and strong collaboration skills.

What is the difference between Mlops vs Data Engineer?

AspectMlopsData Engineer
Primary FocusDeploying, managing, and monitoring machine learning models in productionBuilding and maintaining data pipelines and infrastructure for data processing
Skills & CertificationsMachine learning, DevOps, cloud platforms, scriptingSQL, ETL, data warehousing, programming
Work EnvironmentCollaborates with data scientists, software engineers, and DevOps teamsWorks with data analysts, data scientists, and software developers
Industry UsageAI/ML projects, production environments, cloud servicesData infrastructure, analytics, big data processing

While both Mlops and Data Engineers work closely with data and cloud technologies, Mlops specialists focus on deploying and maintaining machine learning models in production, ensuring their scalability and reliability. Data Engineers primarily build data pipelines and infrastructure to support data analysis and ML workflows. Understanding these distinctions helps organizations assign the right roles for their AI and data projects.

Is MLOps in demand?

MLOps is a rapidly growing field as organizations increasingly adopt machine learning models in production. Professionals with skills in cloud platforms, automation, and tools like Kubernetes and Docker are highly sought after, reflecting strong industry demand for MLOps expertise.

Is MLOps outdated?

MLOps is an evolving field focused on deploying and managing machine learning models efficiently. It remains highly relevant as organizations increasingly adopt AI solutions, with skills in automation, cloud platforms, and monitoring tools in demand. Staying current with new tools and best practices is essential for MLOps professionals.

What is the average salary in MLOps?

The average salary for MLOps engineers typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Professionals with skills in cloud platforms, automation, and machine learning deployment tend to earn higher salaries.

What are the most commonly searched types of Mlops jobs in Texas?

The most popular types of Mlops jobs in Texas are:

What are popular job titles related to Mlops jobs in Texas?

For Mlops jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Mlops jobs in Texas look for?

The top searched job categories for Mlops jobs in Texas are:

What cities in Texas are hiring for Mlops jobs?

Cities in Texas with the most Mlops job openings:

Mlops jobs near you
Infographic showing various Mlops job openings in Texas as of August 2026, with employment types broken down into 92% Full Time, 4% Part Time, and 4% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $140,082 per year, or $67.3 per hour.

MLOps Engineer

Dallas, TX • On-site

Conch Technologies Inc
IT Services • 51 - 200 employees
Learn more about Conch Technologies Incexternal

Contractor

Re-posted 26 days ago

Job description

Hi,
 
Greetings from Conch Technologies
 
Position: MLOps Engineer
Location: Grapevine, TX & Dallas, TX - (Hybrid)
Duration: 6+ Months Contract
 

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 systems
Implement data and model monitoring (drift detection, performance degradation, alerting)
Refactor and productionize data science code into scalable, reusable services
 

Top Skills Details

1. Experience owning the MLOps lifecycle, from data monitoring to refactoring data science code to building a robust ML model lifecycle.
2. Python Engineering
3. CI/CD
4. Experience with MLOps-driven data science outcomes and handling ML Engineering horizontally, helping multiple products and initiatives.
5. Have strong knowledge of Machine Learning, MLOps, MLflow, Kubeflow, Python/R, SQL, Big Data, GCP, and Shell scripting.

With Regards,
 
Chanakya | Sr. IT Recruiter 
Desk: 901-313-3066
Email: chanakya@conchtech.com
LinkedIn: linkedin.com/in/bhadchan
Conch Technologies Inc | www.conchtech.com