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Mlops Engineer Jobs in Texas (NOW HIRING)

IVID TEK INC

MLOps Platform Engineer (SageMaker)

Plano, TX · On-site

$123.98 - $130.87/hr

MLOps Platform Engineer (SageMaker) Duration: 12 months with extension Location: Onsite in Plano, TX 75024 Job ID - 1497588 pay - $90-95/hr W2 (USC/ GC/ H4 / EAD) What we're looking for: Client ...

Incedo Inc

Hadoop Data Engineer

Dallas, TX · On-site

$113K - $136K/yr

Sr. Feature Engineer Dallas,TX/ Pittsburgh, PA / Clevland OH Tech: Data Engineering/Pipeline MLOps Engineering/Pipeline OpenShift Git Linux Programming language: Python SQL Spark Hive Title Skillsets ...

Huntington

MLOps Automation Senior Lead Engineer

Houston, TX · On-site +1

$99K - $130K/yr

The MLOps Automation Engineering Senior Lead will lead a team responsible for building and deploying MLOps Automation for some of Huntington's most valuable and most challenging data-driven projects.

Huntington

MLOps Automation Senior Lead Engineer

Dallas, TX · On-site +1

$93K - $189K/yr

The MLOps Automation Engineering Senior Lead will lead a team responsible for building and deploying MLOps Automation for some of Huntington's most valuable and most challenging data-driven projects.

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Showing results 21-40

All JobsMlops Engineer JobsMlops Engineer Jobs in Texas

Mlops Engineer information

See Texas salary details

$88.4K

$138.7K

$160.9K

How much do mlops engineer jobs pay per year?

As of Sep 2, 2026, the average yearly pay for mlops engineer in Texas is $138,710.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,234.00 and $149,503.00 per year, depending on experience, location, and employer.

What is an MLOps engineer?

An MLOps Engineer is responsible for deploying, monitoring, and maintaining machine learning models in production. They bridge the gap between data science and operations by automating workflows, optimizing infrastructure, and ensuring model reliability. Their role includes CI/CD for ML models, data pipeline management, and performance monitoring. They also work with cloud platforms, containerization, and orchestration tools to scale ML systems efficiently.

What are some common challenges MLOps engineers face in their daily work?

Mlops Engineers often encounter challenges in integrating new machine learning models into existing production systems while ensuring minimal downtime and maintaining data integrity. Managing the scaling and orchestration of models across various cloud or on-prem environments can be complex, requiring close coordination with data scientists and DevOps teams. Staying up to date with rapidly evolving tools and best practices is also essential in this field. Addressing these challenges provides valuable opportunities to innovate and improve both technical processes and team collaboration.

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

To thrive as an Mlops Engineer, you need strong skills in software engineering, machine learning pipelines, and cloud infrastructure, often backed by a degree in computer science, engineering, or a related field. Familiarity with tools such as Docker, Kubernetes, TensorFlow, AWS/GCP/Azure, and CI/CD systems is essential, and certifications like AWS Certified Machine Learning or Kubernetes Administrator are often valued. Effective communication, problem-solving, and teamwork are crucial soft skills for collaborating across data science and IT teams. These abilities enable Mlops Engineers to efficiently deploy, manage, and scale machine learning models in dynamic production environments.

What do you need to be a MLOps engineer?

To become a MLOps engineer, you typically need a strong background in software engineering, machine learning, and cloud platforms. Proficiency in programming languages like Python, experience with containerization tools such as Docker, and knowledge of CI/CD pipelines are essential. Certifications in cloud services and familiarity with tools like Kubernetes and ML frameworks also enhance qualifications.

Who earns more, ML engineer or MLOps engineer?

MLOps engineers typically earn slightly more than ML engineers due to their focus on deploying, maintaining, and scaling machine learning systems, which requires expertise in cloud platforms, automation, and infrastructure. Salary differences can vary based on experience, location, and company size, but MLOps roles often command higher compensation because of their specialized skill set.

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

The most popular types of Mlops Engineer jobs in Texas are:

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

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

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

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What cities in Texas are hiring for Mlops Engineer jobs?

Cities in Texas with the most Mlops Engineer job openings:

Mlops Engineer jobs near you
Infographic showing various Mlops Engineer job openings in Texas as of August 2026, with employment types broken down into 56% Full Time, 11% Temporary, and 33% Contract. Highlights an 100% In-person job distribution, with an average salary of $138,710 per year, or $66.7 per hour.

MLOps Platform Engineer (SageMaker)

Calance US

Plano, TX

Contractor

Medical, Dental, Vision, Life

Re-posted 17 days ago

Job description

We are hiring MLOps Platform Engineer (SageMaker) for a Contract position in Plano, TX
CALL US NOW for immediate consideration! Click Apply on Web or Apply Now to view our recruiter s contact info and reach out today, we d love to speak with you!
=======================================================
• • We will NOT accept 3rd Party (C2C) Contractors * •
=======================================================
JOB DETAILS:
Position:MLOps Platform Engineer (SageMaker)
JOB REF#: 44685 - 1497588
Duration:12+ Months (On-going Contract)
Location:ONSITE - Plano, TX 75024
Pay Rate:OPEN/Market Rate (W2 ONLY)
This role is 100% ONSITE (Must be local or willing to relocate at your own expense)
HOURS: MON- FRI 8am - 5pm
Seeking to hire a MLOps Platform Engineer (Sagemaker) who is expert in Sagemaker and AWS (key skill sets). They will be design, build, and operationalize an enterprise ML platform on AWS SageMaker Unified Studio. You will migrate the organization from a fragmented ML tool chain to a unified, governed platform on AWS Landing Zone 2, covering the full ML lifecycle from data discovery through model deployment and monitoring. They will work with the Enterprise Analytical Data & Integration Team.
RESPONSIBILITIES INCLUDE:
• Set up SageMaker Unified Studio platform domain configuration, project provisioning, persona based roles, and multi-environment (Dev, Prod-UAT, Prod) promotion workflows
• Build MLOps pipelines using SageMaker Pipelines data extraction from Snowflake, preprocessing, training, evaluation, and model registration
• Manage SageMaker Model Registry cross-account model promotion, versioning, immutability, and lineage tracking
• Configure MLflow experiment tracking auto-logging of parameters, metrics, and artifacts
• Set up identity and access management Okta SSO, SailPoint entitlements, persona-based execution roles, service roles for pipelines
• Build model serving real-time SageMaker endpoints and batch prediction workflows
• Set up model monitoring data drift, model drift, performance degradation detection
• Configure data catalog searchable datasets, access-level visibility, access-request workflows, lineage
• Own platform operations observability (CloudWatch, Datadog), logging, custom images, instance availability
REQUIRED SKILLS/EXPERIENCE:
• • MLOps Platform Engineer (Sagemaker) with expertise in SageMaker and AWS (key skill sets).
MANDATORY SKILLS:
• 10+ years of Software Engineering experience focused on cloud infrastructure or ML platform operations.
• 5+ years hands-on experience with AWS, including deep expertise in Amazon SageMaker (Studio Classic Studio, Pipelines, Model Registry, Endpoints, Feature Store)
• 3+ years building and operating production MLOps pipelines (training, versioning, deployment, monitoring, rollback)
• Experience with SageMaker Unified Studio or Studio Classic (domain/project setup, blueprints, multi-tenant configuration)
• MLflow or equivalent experiment tracking
• SageMaker Pipelines or similar workflow orchestration (Airflow, Step Functions)
• Unified Studio is preferred to have but Classic is must
Other skills:
• Infrastructure-as-Code with Terraform, CDK, or CloudFormation
• IAM design for ML platforms execution roles, service roles, cross-account access, Lake Formation, SSO/SAML
• Model serving real-time endpoints, batch transform, auto-scaling, endpoint monitoring
• Snowflake as a data source for ML pipelines
• Kubernetes (EKS) and container orchestration
• Networking and security VPC, security groups, private endpoints, cross-account connectivity
DESIRED SKILLS:
• SageMaker Unified Studio domain provisioning, custom blueprints, project standardization
• SageMaker Feature Store for online/offline feature management
• SageMaker Model Monitor data quality checks, bias detection, drift detection
• AWS Machine Learning Specialty certification
==========================================
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Calance Consultant Benefits Offerings:
- EPO/PPO Medical Plans
- HMO/PPO Dental programs
- Vision - VSP (Vision Plan Summary)
- 401K Retirement vesting program (VOYA)
- Paid Bi-Weekly/Direct Deposit
- Flex Spending Plan
- Voluntary Life, AD&D, STD or LTD plans

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