AI and Machine Learning Engineer

Location: Aguadilla, Puerto Rico (00603); hybrid work with an expectation of working an average of 2 days per week from an HPE office.

Company

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

What you will do

• Research and apply current AI and machine learning technologies, frameworks, and algorithms to solve complex problems and improve models.
• Design, develop, implement, optimize, and deploy machine learning and deep learning models for HPE’s hybrid cloud portfolio.
• Perform data preprocessing, feature engineering, model selection, hyperparameter tuning, training on large datasets, and model performance evaluation.
• Integrate models with existing software systems and infrastructure while addressing scalability, performance, security, and interoperability.
• Monitor deployed models, analyze metrics, fine-tune algorithms, and improve system performance.
• Lead design reviews, establish 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 4–7 years of experience.
• Deep understanding of machine learning algorithms, including linear regression, decision trees, support vector machines, random forests, neural networks, deep learning models, and reinforcement learning.
• Strong foundation in mathematics and statistics, including linear algebra, calculus, probability theory, statistical concepts, and complex machine learning model development.
• Strong programming skills in Python, R, or Java, including production-level code, software engineering best practices, version control systems such as GitHub, and software development methodologies.
• Experience with cloud infrastructure such as AWS or Azure; knowledge of open source technologies and Linux.
• Understanding of DevOps and SRE, plus advanced knowledge of deep learning, neural network architectures, transfer learning, generative models, and optimization algorithms.
• Experience conducting research, evaluating emerging AI and machine learning technologies, and applying state-of-the-art techniques.
• Excellent communication, problem-solving, and critical-thinking skills for collaboration with cross-functional teams and stakeholders.
• Strong knowledge of GitHub Copilot, Cursor, N8N, vibe coding, Windsurf, or similar technologies.

Nice to have

• Knowledge of TensorFlow, PyTorch, scikit-learn, or Keras.
• Deep understanding of statistical modeling, data mining, and data visualization.

Culture & Benefits

• Hybrid work model with flexibility to manage professional and personal needs.
• Health and wellbeing benefits supporting physical, financial, and emotional wellbeing.
• Personal and professional development programs supporting career growth and knowledge expertise.
• Inclusive workplace that values varied backgrounds and individual uniqueness.