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

Cisco

Principal Machine Learning Engineer

Houston, TX

$291K - $369K/yr

Partner with executive leadership, engineering, product, and data science teams to ensure AI ... Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) * Experience ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Cypress, TX

Machine Learning Engineer information

See Cypress, TX salary details

$27.1K

$110.9K

$166.7K

How much do machine learning engineer jobs pay per year?

As of Jul 17, 2026, the average yearly pay for machine learning engineer in Cypress, TX is $110,917.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,400.00 and $133,500.00 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.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Cypress, TX? The most popular types of Machine Learning Engineer jobs in Cypress, TX are:
What are popular job titles related to Machine Learning Engineer jobs in Cypress, TX? For Machine Learning Engineer jobs in Cypress, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Cypress, TX look for? The top searched job categories for Machine Learning Engineer jobs in Cypress, TX are:
What cities near Cypress, TX are hiring for Machine Learning Engineer jobs? Cities near Cypress, TX with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Cypress, TX as of July 2026, with employment types broken down into 91% Full Time, 5% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $110,917 per year, or $53.3 per hour.

Senior Applied Machine Learning Engineer

Hewlett Packard Enterprise Development LP

Spring, TX • On-site

$93K - $127K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Senior Applied Machine Learning Engineer
This role has been designed as 'Hybrid' with an expectation that you will work on average 2 days per week 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 on finding 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 seeking an experienced Senior Applied Machine Learning Engineer with a proven track record of deploying, integrating, and leveraging machine learning and AI solutions in real-world, customer-facing environments. The ideal candidate has worked either directly with clients as part of an AI/ML solutions team or as an end-user of AI/ML products to solve practical business challenges.
Role Overview:
In this role, you will apply your hands-on experience with machine learning and AI technologies to build, optimize, and integrate solutions that address customer needs and improve product performance. You will translate complex data and AI/ML models into accessible, scalable solutions, working closely with cross-functional teams to ensure successful deployment and adoption.
Responsibilities:
Applied ML Development:
  • Design, develop, and deploy machine learning models and AI solutions that address real-world customer problems, focusing on usability, scalability, and performance.

Proof of Concept & Innovation:
  • Rapidly develop demos, POCs, MVPs, and workflows to showcase new AI/ML capabilities that could be integrated into the product or used to improve existing features based on customer feedback or market research. Work in a fast-paced environment to experiment with emerging techniques and tools, ensuring the creation of tangible, functional prototypes that demonstrate practical AI/ML solutions for real-world problems.

Integration & Deployment:
  • Develop and improve integrations of open-source ML/AI tools (e.g., MLFlow, Spark, LangChain, Kubeflow) within production environments, ensuring seamless operation on platforms like Kubernetes.

Solution Optimization:
  • Fine-tune models and algorithms for accuracy, efficiency, and scalability in production settings, including deep learning technologies.

Product & System Enhancement:
  • Translate customer requirements and industry trends into actionable AI/ML solutions that improve product features, data management, and system performance.

Collaboration & Communication:
  • Work closely with product managers, data scientists, and engineering teams to brainstorm, design, and deploy AI/ML solutions, documenting procedures and best practices.

Leadership & Advocacy:
  • Lead efforts in integrating emerging AI tools, mentor junior team members, and communicate progress and challenges to leadership.

Must Have:
  • PhD with at least 2 years of relevant industry experience, or the equivalent (e.g., Master's degree with 4+ years, Bachelor's with 6+ years).
  • Extensive hands-on experience applying machine learning and AI solutions in customer-facing or end-user environments.
  • Proven ability to deploy models in production, ensuring reliability and performance.
  • Experience with open-source ML/AI tools and frameworks.
  • Experience with backend programming languages (Python, Go).
  • Proficiency in developing, using, and maintaining AI agents; proven experience coding agents for automation or decision-making tasks.
  • Excellent written and verbal communication skills, especially in asynchronous collaboration.

Nice to Have:
  • Experience with AI agents and automation.
  • Knowledge of inference deployment and optimization techniques.
  • Familiarity with large-scale data pipelines.
  • Experience with retrieval-augmented systems (e.g., RAG).

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
Job:
Engineering
Job Level:
TCP_04
"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 144,000 - 273,000 in Colorado // 155,500 - 315,000 in California // 137,000 - 315,000 in Texas
The listed salary range reflects base salary. Variable incentives may also be offered."
Information about employee benefits offered in the US can be found at https://myhperewards.com/main/new-hire-enrollment.html
The estimated job application period closure is September 1 2026; this timeline is provided for transparency and internal planning purposes.
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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