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Mlops Engineer Jobs in Spring, TX (NOW HIRING)

Oxy

Advisor IT Systems - AI/ML Ops

Houston, TX

We are seeking a midcareer MLOps / AI Ops Engineer to support the deployment, monitoring, and lifecycle management of machine learning and advanced analytics solutions across upstream Oil & Gas ...

Oxy

Advisor IT Systems - AI/ML Ops

Houston, TX · On-site

We are seeking a mid-career MLOps / AI Ops Engineer to support the deployment, monitoring, and lifecycle management of machine learning and advanced analytics solutions across upstream Oil & Gas ...

Expand Energy

Data Architect

Spring, TX

$58.75 - $75.50/hr

The Data Architect defines and evolves platform capabilities that support analytics, data engineering, machine learning operations (MLOps), and emerging AI-driven use cases, ensuring solutions are ...

Deloitte

AI Engineer Consultant

Houston, TX · Hybrid

... LLMOps/MLOps capabilities (evaluation, monitoring, governance workflows, model/prompt/version ... We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that ...

Deloitte

Senior Forward Deployed Engineer- AWS

Houston, TX · On-site

$99K - $137K/yr

Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt ... Solution Engineering * Build AI-enabled solutions, agentic platforms, and workflows across ...

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Mlops Engineer information

Are MLOps engineers in demand?

MLOps engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

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 does an MLOps engineer do?

An MLOps engineer is responsible for deploying, managing, and maintaining machine learning models in production environments. They work with tools like Docker, Kubernetes, and cloud platforms to automate workflows, ensure model reliability, and monitor performance. Their role combines software engineering, data science, and DevOps practices to streamline the deployment and lifecycle management of machine learning systems.
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Infographic showing various Mlops Engineer job openings in Spring, TX as of August 2026, with employment types broken down into 39% Full Time, and 61% Contract. Highlights an 100% In-person job distribution.

Advisor IT Systems - AI/ML Ops

Oxy

Houston, TX

Full-time

Re-posted 27 days ago

Job description

Oxyproduces,markets and transportsoil and natural gas to maximize value and provide resources fundamental to life. The company leverages its global leadership incarbon managementto advance lower-carbon technologies and products. Headquartered in Houston, Oxy primarily operates in the United States, Middle East and North Africa. To learn more, visitOxy

Oxy strives to attract and retain talented employees by investing in their professional development and providing rewarding opportunities for personal growth. Our goal is to meet the highest employer standards by ensuring the health and safety of our employees, protecting the environment and positively impacting our communities where we do business.

We are seeking a midcareer MLOps / AI Ops Engineer to support the deployment, monitoring, and lifecycle management of machine learning and advanced analytics solutions across upstream Oil & Gas operations. This role bridges data science, cloud engineering, and operations to ensure reliable, scalable, and secure AI systems in production.

Key Responsibilities

  • Design, build, and maintain MLOps pipelines and platforms for model training, deployment, monitoring, and retraining using AWS.

  • Operationalize ML models for upstream use cases (e.g., production optimization, subsurface modeling, drilling analytics).

  • Implement CI/CD, model versioning, experiment tracking, and performance monitoring.

  • Collaborate with data scientists, data engineers, and domain experts to move models from development to production.

  • Ensure reliability, observability, governance, and compliance of ML systems.

  • Troubleshoot production issues related to data, models, and infrastructure.

Required Qualifications

  • 5+ years of experience in data engineering, software engineering, MLOps, or AI Ops.

  • Good grasp of software architecture principles and systems design

  • Strong proficiency in Python for productiongrade ML workflows.

  • Handson experience with AWS (e.g., S3, EC2, EKS/ECS, SageMaker, Lambda, CloudWatch).

  • Experience deploying and supporting ML models in production environments.

  • Familiarity with CI/CD tools, Docker, and Kubernetes.

  • Understanding of ML lifecycle management, model monitoring, and data drift.

Preferred Qualifications

  • Experience supporting analytics or ML solutions in upstream Oil & Gas or energy.

  • Knowledge of timeseries, forecasting, or physicsinformed ML workloads.

  • Experience with infrastructureascode (Terraform, CloudFormation).

Recruitment Fraud
It has come to our attention various individuals and/or organizations are contacting people falsely pretending to recruit on behalf of Oxy. Please be aware that these recruiting scams and communications do not originate nor are they associated with our recruitment process. All Oxy job postings and offers will require a completed application through our company website.
Oxy does not charge a fee at any stage of the recruiting process. We will never:
Ask you to pay for applications, interviews, meetings, processing, training or for any other fees
Use recruiting or placement agencies that charge candidates an advance fee of any kind or
Request personal information such as passport and bank account details at an early stage of our recruitment process.
We recommend against responding to unsolicited business propositions or offers from people you don't know. Do not disclose your personal or financial details. If you believe you have been the victim of a recruiting scam, please contact your local police department.


All qualified applicants will receive consideration for employment without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.

Oxy logo

About Oxy

Sourced by ZipRecruiter

For 100 years, Oxy has developed extensive assets, infrastructure, expertise and technology to fuel progress and improve lives around the world. Now we’re leveraging these resources to help solve the planet’s most pressing environmental challenges. We want to be part of the solution, so we're taking bold steps to innovate new technologies for a low-carbon future. Oxy produces energy and essential products to sustain and improve life on our planet. Our experienced teams, located in the United States, Middle East, Africa and Latin America, are committed to safe and efficient operations and products, and to reducing our carbon footprint and helping others do the same.

Industry

Oil and gas extraction

Company size

10,000+ Employees

Headquarters location

Houston, TX, US

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