Senior Applied Machine Learning Engineer
Hewlett Packard Enterprise · Spring, Texas, United States of America ·
- Seniority
- Senior
- Category
- ML ai
- Experience
- 2+ years
Hewlett Packard Enterprise · Spring, Texas, United States of America ·
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.
Job:
EngineeringJob 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.
Information about employee benefits offered in the US can be found at
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.
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