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Principal AI & Machine Learning Engineer

Spring, Texas, United States of America

Pay
USD 178,000–361,000/yearLocation-specific pay — pay source
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 178,000 - 361,000 in California // 157,000 - 361,000 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
Read the full posting
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Design, develop and deploy AI apps, microservices and APIs on Kubernetes

  • Build end-to-end AI pipelines with deployment, monitoring and versioning

  • Lead and mentor AI/ML engineers, running code reviews and setting best practices

  • Evaluate and adopt new AI tools, frameworks and LLM technologies

  • Write technical documentation, deployment runbooks and SOPs

From the employer’s posting
Design, develop, and deploy AI applications, microservices, and APIs on Kubernetes-based infrastructure
Build and maintain end-to-end AI pipelines covering deployment, monitoring, versioning, and continuous improvement
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
Establish and maintain technical documentation, deployment runbooks and SOPs

What you’ll bring

All qualifications

Core experience

  • 12+ years of hands-on experience in software engineering, with a strong focus on AI/ML application development and deployment.
  • Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, or a related field.
  • 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.
  • Hands-on experience with CI/CD pipelines and tools such as GitOps, Docker, Jenkins, or GitHub Actions.
Qualification wording
12+ years of hands-on experience in software engineering, with a strong focus on AI/ML application development and deployment.
Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, or a related field.
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.
Hands-on experience with CI/CD pipelines and tools such as GitOps, Docker, Jenkins, or GitHub Actions.
Education & alternatives
Education - Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, or a related field. #unitedstates

Tools in this posting

  • Python
  • AWS
  • Azure
  • Docker
  • GCP
  • Grafana
  • Kubernetes
  • MLflow
  • Airflow
  • FastAPI
  • Flask
Source — Tool mentions in context
- 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.
- 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.
- 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.
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.
- 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).
- 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.

About Hewlett Packard Enterprise

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.

In the employer’s words · Read in context

Posting record

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Status in our records
Live
First seen by us
Aug 20, 2026 · 72 days ago
Recorded sightings
112
Last seen by us
Oct 31, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

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Job description

View original posting ↗

Principal AI & Machine Learning Engineer

  

This 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 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 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, TX or Sunnyvale, CA

Onsite "Hybrid" 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


Accessibility


HPE is committed to creating an inclusive and accessible workplace and encourages applications from all qualified individuals, including those with disabilities. If you believe you require accommodation during any stage of the application or interview process, please submit your request by completing our secure form linked here.


Note: This option is reserved for applicants needing assistance/reasonable accommodation related to a disability.

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 178,000 - 361,000 in California // 157,000 - 361,000 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

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.

Source details

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Pay
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 178,000 - 361,000 in California // 157,000 - 361,000 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
Location & working pattern

Spring, Texas, United States of America

Location: Spring, TX or Sunnyvale, CA Onsite "Hybrid" work required Key Responsibilities
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