AI and ML Solution Architect

Hewlett Packard Enterprise

. Research and stay current with advancements in 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 optimizing machine learning models and algorithms, with a strong foundation in mathematics and statistics. Proficient in Python, R, or Java, and experienced in deploying scalable AI/ML solutions in production environments.

Highest-signal resume keywords

Machine Learning AlgorithmsDeep Learning ModelsPython 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 MiningStatistical ModelingFeature EngineeringHyperparameter TuningModel SelectionData VisualizationNatural Language ProcessingReinforcement LearningTransfer Learning

Soft Skills

Excellent CommunicationProblem-SolvingCritical ThinkingMentorshipCollaboration

Tools & Technologies

TensorFlowPyTorchSci-kit LearnGitProduction-Level Code

Industry Keywords

Artificial IntelligenceMachine LearningData ScienceQuantitative DisciplineSoftware Engineering Best Practices

Tech Stack

Tools & technologies

JavaPythonPyTorchTensorflow

About the role

Key responsibilities & impact

Research and stay current with advancements in AI and machine learning technologies, frameworks, and algorithms
Explore cutting-edge techniques to solve complex problems and improve existing models
Collaborate with cross-functional teams to understand business requirements and design scalable, efficient, and robust AI/ML solutions
Develop, implement, and optimize machine learning models and algorithms
Perform data preprocessing, feature engineering, model selection, hyperparameter tuning, and training on large datasets
Monitor and improve model performance and accuracy
Deploy machine learning models into production environments with scalability, performance, and security considerations
Integrate models with existing software systems and infrastructure
Monitor deployed models, collect metrics, analyze data, fine-tune models, and optimize algorithms
Lead comprehensive design review sessions and align discussions with project requirements and best practices
Mentor and provide feedback to 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
Address and resolve challenges proactively
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, including linear regression, decision trees, support vector machines, random forests, deep learning models, and reinforcement learning
Strong foundation in mathematics and statistics, including linear algebra, calculus, probability theory, and statistical concepts
Proficiency in Python, R, or Java
Experience developing production-level code
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, or sci-kit
Advanced knowledge and experience in deep learning, including convolutional neural networks, recurrent neural networks, and transformers
Experience with transfer learning, generative models, and deep-learning optimization algorithms
Experience conducting AI and machine learning research and applying state-of-the-art techniques
Excellent communication, problem-solving, and critical-thinking skills
Strong programming skills and 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