AI and Machine Learning Engineer

Description

The company is a global edge-to-cloud business that helps customers connect, protect, analyze and act on their data and applications, from edge to cloud.

This is a senior engineering role in the Engineering function (job level TCP03) where you lead AI and machine learning initiatives across the hybrid cloud portfolio.

The role suits someone who works well in a demanding environment with a quick pace.

Responsibilities

• Keep up with the latest AI and machine learning research, frameworks and algorithms, and test new techniques on hard problems and existing models.
• Work with cross-functional teams to understand business needs, then choose the algorithms, models and frameworks and design a system that scales, runs efficiently and holds up under load.
• Build and improve machine learning models and algorithms, covering data preparation, feature engineering, model selection, hyperparameter tuning and training on large datasets, and keep raising accuracy.
• Develop and program integrated software algorithms that structure and analyze structured and unstructured data, using large-scale computing frameworks and modeling environments.
• Turn customer requirements and industry trends into AI and machine learning products, solutions and system improvements.
• Deploy models to production with attention to scale, performance and security, and integrate them with existing software and infrastructure so they run smoothly together.
• Monitor deployed models, collect metrics, analyze results, and then tune models, algorithms and system performance.
• Define performance metrics, write installation and maintenance documentation, and handle testing and debugging.
• Apply data mining, data modeling, natural language processing and machine learning to extract insights from datasets.
• Lead design reviews and regular team meetings, and set design and implementation standards with the engineering manager and team lead.
• Mentor and give feedback to junior and mid-level engineers, and provide technical leadership and guidance.
• Present strategic reports and recommendations to senior stakeholders, covering both technical and business aspects.
• Act as a subject matter expert and partner with functional and technical project teams, using your own judgment to pick the best approach.

Requirements

• A bachelor's or master's degree in computer science, engineering, data science, machine learning, artificial intelligence or a closely related quantitative field.
• Typically 4-7 years of experience.
• A deep understanding of machine learning algorithms, including linear regression, decision trees, support vector machines, random forests, neural networks and reinforcement learning, plus skill in model selection, hyperparameter tuning and performance evaluation.
• A strong grounding in linear algebra, calculus, probability and statistics, with the ability to develop complex models and algorithms.
• Proficiency in Python, R or Java, experience writing production-level code, and familiarity with version control such as GitHub and standard software engineering and development practices.
• A strong understanding of tools like GitHub Copilot, Cursor, N8N, Windsurf and vibe coding, or similar technologies.
• Experience with cloud infrastructure such as AWS or Azure.
• Knowledge of open source software and Linux.
• An understanding of DevOps and SRE practices.
• Advanced knowledge of deep learning, including convolutional and recurrent neural networks and transformers, plus transfer learning, generative models and deep learning optimization algorithms.
• Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch or sci-kit.
• Ongoing research experience, including exploring new technologies and applying state-of-the-art techniques to complex problems.
• Excellent communication skills for working with cross-functional teams and stakeholders, and strong problem-solving and critical thinking skills to guide projects and make strategic decisions.
• Plus: knowledge of Keras and similar libraries.
• Highly preferred: a deep understanding of statistical modeling, data mining and data visualization.

Conditions

This is a hybrid role, with an average of 2 days per week in a company office.

The position is based in Puerto Rico.

The company is an equal opportunity employer and makes hiring decisions based on qualifications, merit and business need.

Benefits

• Health and wellbeing benefits covering physical, financial and emotional wellbeing for employees and their families.
• Career development programs to help you reach your goals, such as becoming a recognized expert in your field or moving into another division.
• Flexibility to manage your work and personal needs.