AI and ML Solution Architect

Location: Hybrid in Spring, Texas, United States of America; average of 2 days per week required in an HPE office.

Base salary: USD 141,000–325,000 annual in Texas; variable incentives may also be offered.

Company

hirify.global is a global edge-to-cloud technology company developing solutions that connect, protect, analyze, and act on data and applications.

What you will do

• Research and apply current AI and machine learning technologies, frameworks, algorithms, and state-of-the-art techniques.
• Translate business requirements into scalable, efficient, robust AI/ML architectures in collaboration with cross-functional teams.
• Develop, optimize, and evaluate machine learning models through data preprocessing, feature engineering, model selection, hyperparameter tuning, and large-scale training.
• Deploy models to production, integrate them with existing software and infrastructure, and address scalability, performance, security, and interoperability.
• Monitor deployed models, analyze metrics, fine-tune algorithms, and improve system performance and accuracy.
• Lead design reviews and meetings, establish design and implementation standards, mentor junior and mid-level team members, and present technical recommendations to senior stakeholders.

Requirements

• Bachelor’s or master’s degree in computer science, engineering, data science, machine learning, artificial intelligence, or a closely related quantitative discipline.
• Typically 7–10 years of experience.
• Deep knowledge of machine learning algorithms, including linear regression, decision trees, support vector machines, random forests, neural networks, deep learning models, and reinforcement learning.
• Proficiency in model selection, hyperparameter tuning, and evaluation of model performance using appropriate metrics.
• Strong foundation in mathematics and statistics, including linear algebra, calculus, probability theory, and statistical concepts.
• Strong programming skills in Python, R, or Java, including production-level code, software engineering practices, version control systems such as Git, and software development methodologies.
• Experience with popular 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, transformers, transfer learning, generative models, and optimization algorithms.
• Experience conducting AI/ML research, exploring emerging technologies, and applying advanced techniques to complex problems.
• Excellent communication, problem-solving, and critical-thinking skills for collaborating with cross-functional teams, guiding projects, and making strategic decisions.
• Experience providing technical leadership, mentorship, and guidance to junior team members.

Nice to have

• Knowledge of Keras and additional machine learning libraries or frameworks.
• Deep understanding of statistical modeling, data mining, and data visualization.

Culture & Benefits

• Hybrid work model with flexibility to manage work and personal needs.
• Health, financial, and emotional wellbeing benefits for employees and their loved ones.
• Personal and professional development programs supporting career growth and specialization.
• Inclusive workplace that values varied backgrounds and individual uniqueness.
• Accessibility accommodations are available during the application and interview process.