AI and ML Solution Architect

Hewlett Packard Enterprise

. Research and stay current with AI and machine learning technologies, frameworks, and algorithms .

Posted 10/22/2026full-timeUnited StatesSeniorLead💰 $141,000 - $325,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing and deploying scalable AI and machine learning solutions, with a strong foundation in algorithms, model optimization, and statistical analysis. Proven ability to lead teams, mentor peers, and communicate complex concepts effectively to stakeholders.

Highest-signal resume keywords

Machine Learning AlgorithmsDeep Learning TechniquesPython ProgrammingTensorFlow FrameworkData Preprocessing

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Machine LearningData MiningModel SelectionHyperparameter TuningStatistical ModelingData VisualizationFeature EngineeringNatural Language ProcessingProduction-Level CodingMathematics and Statistics

Soft Skills

Excellent CommunicationProblem-SolvingCritical ThinkingMentorshipCollaboration

Tools & Technologies

TensorFlowPyTorchSci-KitGitSoftware Development Methodologies

Industry Keywords

Artificial IntelligenceMachine LearningData ScienceQuantitative DisciplineEmerging Techniques

Tech Stack

Tools & technologies

JavaKerasPythonPyTorchTensorflow

About the role

Key responsibilities & impact

Research and stay current with AI and machine learning technologies, frameworks, and algorithms
Collaborate with cross-functional teams to understand requirements and architect scalable, efficient, and robust AI/ML solutions
Develop, implement, optimize, and monitor machine learning models and algorithms
Perform data preprocessing, feature engineering, model selection, hyperparameter tuning, and training on large datasets
Deploy machine learning models into production with scalability, performance, and security considerations
Integrate models with existing software systems and infrastructure
Monitor deployed-model performance, analyze metrics, fine-tune models, optimize algorithms, and improve system performance
Lead comprehensive design review sessions and mentor junior and mid-level team members
Set design and implementation standards with the engineering manager and team lead
Lead meetings and foster a collaborative team environment
Provide technical leadership, mentorship, and guidance
Develop and deliver strategic presentations and reports to senior stakeholders
Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from datasets

Requirements

What you’ll need

Bachelor's or master's degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline
Typically 7–10 years’ experience
Deep understanding of machine learning algorithms, model selection, hyperparameter tuning, and model-performance evaluation
Strong foundation in mathematics and statistics, including linear algebra, calculus, probability theory, and statistical concepts
Proficiency in Python, R, or Java
Production-level coding experience and familiarity with software engineering best practices, version control systems such as Git, and software development methodologies
Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, sci-kit, and Keras; TensorFlow, PyTorch, or sci-kit are essential
Advanced knowledge and experience in deep learning, including CNNs, RNNs, transformers, transfer learning, generative models, and optimization algorithms
Experience conducting AI/ML research and applying emerging, state-of-the-art techniques
Excellent communication, problem-solving, and critical-thinking skills
Strong programming skills with expertise in Python, R, or Java
Deep understanding of statistical modeling, data mining, and data visualization is highly preferred

Benefits

Comp & perks

Comprehensive benefits supporting physical, financial, and emotional wellbeing
Personal and professional development programs
Flexible work arrangements to manage work and personal needs
Inclusive workplace and accessibility accommodations
Variable incentives may also be offered