Senior Applied Machine Learning Engineer

Hewlett Packard Enterprise

Senior Applied Machine Learning Engineer building and integrating AI/ML solutions at Hewlett Packard Enterprise. Focus on deploying models and working with cross-functional teams to improve customer outcomes.

Posted 7/15/2026full-timeSpring • California, Colorado, Texas • 🇺🇸 United StatesSenior💰 $144,000 - $315,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying machine learning models and AI solutions, with a strong focus on usability, scalability, and performance. Proficient in integrating open-source ML/AI tools and collaborating with cross-functional teams to translate customer needs into actionable solutions.

Highest-signal resume keywords

Machine Learning Model DevelopmentAI Solution DeploymentOpen-Source ML/AI ToolsBackend Programming (Python, Go)Excellent Communication Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningAI SolutionsModel DeploymentDeep LearningAutomation Coding

Soft Skills

Written CommunicationVerbal Communication

Tools & Technologies

MLFlowSparkLangChainKubeflowKubernetes

Certifications & Qualifications

PhDMaster’s DegreeBachelor's Degree

Industry Keywords

Customer-Facing SolutionsEnd-User EnvironmentsProduction EnvironmentsData ManagementSystem Performance

Tech Stack

Tools & technologies

GoKubernetesPythonSpark

About the role

Key responsibilities & impact

Design, develop, and deploy machine learning models and AI solutions that address real-world customer problems, focusing on usability, scalability, and performance.
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.
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.
Fine-tune models and algorithms for accuracy, efficiency, and scalability in production settings, including deep learning technologies.
Translate customer requirements and industry trends into actionable AI/ML solutions that improve product features, data management, and system performance.
Work closely with product managers, data scientists, and engineering teams to brainstorm, design, and deploy AI/ML solutions, documenting procedures and best practices.
Lead efforts in integrating emerging AI tools, mentor junior team members, and communicate progress and challenges to leadership.

Requirements

What you’ll need

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.

Benefits

Comp & perks

Health & Wellbeing
Personal & Professional Development
Unconditional Inclusion