Engineering Analyst

As an Engineering Analyst, you will contribute to the design, development, and implementation of software and AI-driven solutions that support business operations, decision-making, and scalable technology platforms. You will work closely with software engineers, data scientists, and business stakeholders to build high-quality applications, analyze data, and help deliver reliable, secure, and impactful solutions in a fast-paced, collaborative environment.

Responsibilities

• Design, develop, test, and support software applications, systems, and AI-powered tools.
• Collaborate with engineers, data scientists, product stakeholders, and business teams to understand requirements and deliver practical solutions.
• Analyze large datasets to identify insights and support the development of machine learning and data-driven applications.
• Assist in building, optimizing, and evaluating AI/ML models for performance, scalability, and accuracy.
• Write clean, maintainable, and efficient code following engineering best practices and coding standards.
• Troubleshoot and debug software and AI system issues, providing timely resolutions.
• Participate in code reviews, testing, and documentation to support knowledge sharing and code quality.
• Contribute to the continuous improvement of development processes, tools, and workflows.
• Stay up to date with emerging technologies, AI frameworks, and industry trends.

We are seeking a curious, driven, and technically strong Software Engineering Analyst to join our Container Platform Engineering team at Millennium. This role is designed for candidates in their final year of study who are available to start full-time in September 2026., * Final-year student or recent graduate in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related field.

• 0-1 years of relevant experience through academic projects, internships, placements, or early professional experience.
• Strong programming skills in at least one relevant language such as Python, Java, C++, C#, or JavaScript.
• Familiarity with software engineering fundamentals, including testing, debugging, version control, and coding best practices.
• Exposure to machine learning frameworks or libraries such as PyTorch, TensorFlow, or Scikit-learn.
• Experience or familiarity with SQL, databases, and data analysis tools such as Pandas or similar technologies.
• Understanding of core AI/ML concepts such as supervised and unsupervised learning, model evaluation, NLP, or computer vision.
• Familiarity with software development methodologies such as Agile or Scrum is a plus.
• Strong problem-solving skills, attention to detail, and willingness to learn.
• Excellent communication and teamwork abilities.