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Machine Learning Engineer Jobs in Spring, TX (NOW HIRING)

AI Lead 11+ years of exp

Houston, TX · On-site

$133K - $164K/yr

Proven experience as an AI Engineer, Machine Learning Engineer, or similar role, with a portfolio of delivered AI/Gen AI solutions. * Proficiency in AI platforms and tools such as Azure OpenAI ...

PMP, CSM, or AI certifications (e.g., Google Professional Machine Learning Engineer) preferred. * 5+ years in program/project management, with 3+ years focused on AI/ML, cloud platforms (AWS, Azure ...

AI Solutions Architect

Houston, TX

$60.25 - $79.25/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

Sr. ML Ops Engineer

Spring, TX · On-site

$93K - $127K/yr

They are seeking a Senior ML Ops Engineer to build and operate platforms and pipelines that support machine learning models and data products, while collaborating with various teams to deliver ...

Sr. ML Ops Engineer

Spring, TX · On-site

$96K - $132K/yr

... Engineers to identify and define requirements ... Design, develop, and support machine learning operations (MLOps) platforms and tools in support of ...

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Sr. MLOps Engineer

Spring, TX · On-site

$110K/yr

As a ML Ops engineer you will be responsible for building and operating the platforms, pipelines ... Design, develop, and support machine learning operations (MLOps) platforms and tools in support of ...

Principal Data Engineer

Houston, TX · On-site

$106K - $127K/yr

This position demands a blend of cloud data engineering, systems engineering, data integration, and machine learning systems knowledge to enhance GST's data capabilities, supporting advanced ...

Software Engineer in Data Science

Houston, TX · On-site

$109K - $131K/yr

The individual will work both with our data scientists and machine learning engineers but will also need to directly engage with the commercial teams (across trading, operations, support functions ...

Software Engineer in Data Science

Houston, TX · On-site +1

$109K - $131K/yr

The individual will work both with our data scientists and machine learning engineers but will also need to directly engage with the commercial teams (across trading, operations, support functions ...

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Showing results 1-20

Machine Learning Engineer information

See Spring, TX salary details

$28K

$114.6K

$172.2K

How much do machine learning engineer jobs pay per year?

As of Jul 9, 2026, the average yearly pay for machine learning engineer in Spring, TX is $114,590.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,300.00 and $137,900.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Spring, TX? The most popular types of Machine Learning Engineer jobs in Spring, TX are:
What are popular job titles related to Machine Learning Engineer jobs in Spring, TX? For Machine Learning Engineer jobs in Spring, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Spring, TX look for? The top searched job categories for Machine Learning Engineer jobs in Spring, TX are:
What cities near Spring, TX are hiring for Machine Learning Engineer jobs? Cities near Spring, TX with the most Machine Learning Engineer job openings:

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

Hewlett Packard Enterprise Development LP

Spring, TX • On-site

Full-time

Posted 7 days ago


Job description

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

  • 10+ 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.