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Senior Applied Machine Learning Engineer
Hewlett Packard EnterprisePosted 10/19/2026full-timeDurham • North Carolina • United StatesSenior💰 $141,000 - $325,000 per yearWebsite
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing, developing, and deploying machine learning models and AI solutions, with a strong focus on integrating open-source tools and ensuring operational efficiency in production environments. Proven ability to mentor team members and communicate effectively with cross-functional teams.
Highest-signal resume keywords
Machine Learning Model DevelopmentAI Solutions DeploymentPython ProgrammingOpen-Source ML/AI ToolsKubernetes Operations
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Design, develop, and deploy machine learning models and AI solutions for real-world customer problems
- Rapidly develop demos, proofs of concept, MVPs, and workflows showcasing new AI/ML capabilities
- Experiment with emerging AI/ML techniques and tools to create functional prototypes
- Develop and improve integrations of open-source ML/AI tools such as MLFlow, Spark, LangChain, and Kubeflow in production environments
- Ensure seamless operation on platforms such as Kubernetes
- Fine-tune models and algorithms for accuracy, efficiency, and scalability, including deep learning technologies
- Translate customer requirements and industry trends into AI/ML solutions improving product features, data management, and system performance
- Collaborate with product managers, data scientists, and engineering teams to design and deploy solutions
- Document procedures and best practices
- Lead integration efforts for emerging AI tools
- Mentor junior team members
- Communicate progress and challenges to leadership
Requirements
What you’ll need- PhD with at least 2 years of relevant industry experience, or equivalent: Master’s degree with 4+ years or Bachelor's degree 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 including Python and 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
- Nice to have: knowledge of inference deployment and optimization techniques
- Nice to have: familiarity with large-scale data pipelines
- Nice to have: experience with retrieval-augmented systems such as RAG
Benefits
Comp & perks- Comprehensive health and wellbeing benefits supporting physical, financial, and emotional wellbeing
- Personal and professional development programs
- Flexible work arrangements to manage work and personal needs
- Inclusive workplace culture
- Reasonable accommodation during application or interview process for applicants with disabilities
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningAI SolutionsDeep Learning TechnologiesModel Fine-TuningBackend Programming LanguagesAutomation CodingAI Agent DevelopmentInference Deployment TechniquesData Pipeline ManagementIntegration of ML Tools
Soft Skills
Excellent Communication SkillsMentoringCollaboration
Tools & Technologies
MLFlowSparkLangChainKubeflowKubernetes
Certifications & Qualifications
PhDMaster's DegreeBachelor's Degree
Industry Keywords
Customer-Facing SolutionsEnd-User EnvironmentsEmerging AI TechniquesProofs of ConceptMVP Development