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Senior Mlops Engineer Jobs in Spring, TX (NOW HIRING)

Sr Software Development Eng

Houston, TX

$116K - $154K/yr

Position Specific Description As a Senior Software Engineer in an MLOps and platform-focused role, you will be responsible for designing, optimizing, and operating software platforms that support ...

Sr Software Development Eng

Houston, TX · On-site

$116K - $154K/yr

Position Specific Description As a Senior Software Engineer in an MLOps and platform-focused role, you will be responsible for designing, optimizing, and operating software platforms that support ...

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

Experience with cloud platforms (AWS preferred) and modern MLOps practices: containerization ... and senior management * Genuine intellectual curiosity about commodities markets, global energy ...

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

Experience with cloud platforms (AWS preferred) and modern MLOps practices: containerization ... and senior management * Genuine intellectual curiosity about commodities markets, global energy ...

Showing results 21-40

Senior Mlops Engineer information

See Spring, TX salary details

$52.9K

$112.6K

$163.3K

How much do senior mlops engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for senior mlops engineer in Spring, TX is $112,622.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,000.00 and $127,700.00 per year, depending on experience, location, and employer.

What is a senior MLOps engineer?

A Senior MLOps Engineer is an experienced professional who bridges the gap between data science, machine learning, and software engineering. They are responsible for designing, deploying, and maintaining scalable machine learning systems in production environments. Their role involves automating workflows, monitoring model performance, ensuring reproducibility, and managing the infrastructure needed to support machine learning operations. Senior MLOps Engineers also collaborate with data scientists, software developers, and IT teams to ensure smooth integration and continuous delivery of ML models. They play a crucial role in making machine learning solutions reliable, efficient, and scalable for business applications.

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

To thrive as a Senior MLOps Engineer, you need deep expertise in machine learning workflows, software engineering, and cloud infrastructure, typically supported by a degree in computer science or related fields. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, and platforms such as AWS, GCP, or Azure, as well as certifications in cloud or DevOps, are highly valuable. Strong problem-solving, collaboration, and communication skills set standout professionals apart in this role. These skills and qualities are crucial to ensuring robust, scalable, and efficient deployment of machine learning models in production environments.

What are some common challenges senior MLOps engineers face when deploying machine learning models to production environments?

Senior MLOps Engineers often encounter challenges such as managing model versioning, ensuring reproducibility, and scaling deployments across diverse infrastructure. Balancing the needs of data scientists for experimentation with the stability and reliability requirements of production systems can be complex. Additionally, integrating continuous integration and continuous deployment (CI/CD) pipelines for ML workflows and monitoring model performance post-deployment are ongoing responsibilities. Collaboration with data scientists, software engineers, and IT operations is crucial to address these challenges and maintain robust, efficient ML systems.

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

AspectSenior Mlops EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, Engineering, or related; experience with ML deployment toolsBachelor's/Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in productionFocus on data analysis, model development, and insights generation
Industry UsageUsed in tech, finance, healthcare for ML deploymentUsed across industries for data analysis and modeling

The main difference is that Senior Mlops Engineers specialize in deploying and maintaining machine learning models in production environments, while Data Scientists focus on developing models and analyzing data. Both roles require strong technical skills, but their day-to-day tasks and focus areas differ significantly.

Are senior MLOps engineers in demand?

Senior MLOps engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are valued for their expertise in deploying, managing, and scaling machine learning models using tools like Kubernetes, Docker, and cloud platforms. The role often requires strong skills in automation, CI/CD pipelines, and cloud infrastructure, making experienced professionals highly sought after.

How much do senior MLOps engineers make?

Senior MLOps engineers typically earn between $120,000 and $180,000 annually, depending on experience, location, and company size. They often have expertise in cloud platforms, automation tools, and machine learning deployment pipelines, which can influence salary levels.

What are popular job titles related to Senior Mlops Engineer jobs in Spring, TX?

For Senior Mlops Engineer jobs in Spring, TX, the most frequently searched job titles are:

What job categories do people searching Senior Mlops Engineer jobs in Spring, TX look for?

The top searched job categories for Senior Mlops Engineer jobs in Spring, TX are:

What cities near Spring, TX are hiring for Senior Mlops Engineer jobs?

Cities near Spring, TX with the most Senior Mlops Engineer job openings:

Infographic showing various Senior Mlops Engineer job openings in Spring, TX as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $112,622 per year, or $54.1 per hour.

Senior Principal AI & Machine Learning Engineer, Spring, Texas, Onsite

Hewlett Packard Enterprise Development LP

Spring, TX • On-site

$111K - $154K/yr

Full-time

Re-posted 6 days ago


Hewlett Packard Enterprise rating

8.4

Company rating: 8.4 out of 10

Based on 26 frontline employees who took The Breakroom Quiz

35th of 161 rated electronics manufacturers


Job description

Senior Principal AI & Machine Learning Engineer, Spring, Texas, OnsiteThis role has been designed as ''Onsite' with an expectation that you will primarily work from an HPE office.

Who We Are:

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today's complex world.Our culture thrives onfinding new and better ways to accelerate what's next.We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs.We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you.Open up opportunities with HPE.

Job Description:

We are looking for an experienced Principal AI Engineer to drive the design, development, and deployment of AI/ML-powered applications. Candidate should have strong hands-on experience in application development, lead and mentor a team of AI developers, define best practices, and deliver scalable, production grade AI solutions aligned with business goals.

Location: Spring, Texas

Onsite daily work required

Key Responsibilities

  • Design, develop, and deploy AI applications, microservices, and APIs on Kubernetes-based infrastructure, ensuring scalability, reliability, and performance across development, staging, and production environments.
  • Build and maintain end-to-end AI pipelines covering deployment, monitoring, versioning, and continuous improvement using modern MLOps/AIOps tools and practices.
  • Lead and mentor a team of AI/ML engineers, conduct code reviews, and define best practices.
  • Continuously evaluate and adopt emerging AI tools, frameworks, LLM technologies, and open-source solutions to enhance platform capabilities and team productivity.
  • Collaborate closely with Business Analysts, Architect and technical teams to align AI engineering efforts with business objectives and ensure secure, compliant solutions.
  • Establish and maintain technical documentation, deployment runbooks and SOPs

Required Qualifications

  • 12+ years of hands-on experience in software engineering, with a strong focus on AI/ML application development and deployment.
  • Expertise in Kubernetes - container orchestration, Helm charts, pod management, scaling, and troubleshooting.
  • Strong experience with MLOps/AIOps tools and practices (e.g., MLflow, Kubeflow, Airflow, model registries, monitoring frameworks).
  • Hands-on experience with cloud platforms - Azure, AWS, or GCP, including their AI services.
  • Strong programming skills in Python; familiarity with FastAPI, Flask, or similar frameworks is mandatory.
  • Hands-on experience with CI/CD pipelines and tools such as GitOps, Docker, Jenkins, or GitHub Actions.
  • Lead and mentor development teams, drive delivery, and manage technical priorities.
  • Experience working with Agentic and GenAI frameworks and vector databases etc.
  • Experience with observability and monitoring tools (Prometheus, Grafana, OpenTelemetry) for AI workloads.
  • Good understanding of AI security, responsible AI principles, and governance frameworks.

Education

  • Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, or a related field.

#unitedstates

What We Can Offer You:

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have - whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.

Let's Stay Connected:

Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.

#unitedstates#operations

Job:

Engineering

Job Level:

TCP_05"The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level.
- United States of America: Annual Salary USD 152,000 - 349,000 in Texas
The listed salary range reflects base salary. Variable incentives may also be offered.""The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level.

Information about employee benefits offered in the US can be found at https://myhperewards.com/main/new-hire-enrollment.html

HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

Recruitment Fraud Alert

We have become aware of an increase in fraudulent recruitment activities in which individuals impersonate our company or authorized recruitment agencies to offer fake employment opportunities. These scams may occur through false websites, emails, social media, or chat-based applications and often aim to obtain personal information or money. Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge a candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. We also never request personal information such as back account details, Social Security numbers, or national IDs via social media or chat applications.

All legitimate job opportunities will come through official company channels, and candidates are responsible for verifying the credentials of any third party claiming to represent the company. Any reliance on fraudulent communication is at the individual's own risk, and HPE disclaims legal liability for any resulting damages. If you suspect recruitment fraud, do not share personal information or make any payments and report the incident to your local authorities immediately.


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