Machine Learning Engineer - AI & Intelligent Systems

About Amplink Technologies

Amplink Technologies has created the Amplink modelling platform, a proprietary software solution designed by energy specialists to simulate market, grid, and system integration dynamics. This platform merges rich data collections with a MarketBrain AI tool crafted by industry professionals, providing straightforward analytics for intricate energy issues. Its user-friendly interface assists governments, utility providers, and investors in data-focused planning and decision-making processes, tailored to energy systems undergoing transition by assessing risks, opportunities, and long-term behaviors.

Role Overview

The position of Machine Learning Engineer – AI & Intelligent Systems at Amplink Technologies is a permanent, on-location role in Adelaide, SA. The selected candidate will be responsible for designing, developing, and deploying machine learning algorithms that support MarketBrain AI and improve the Amplink modelling platform's capabilities. Collaboration with energy domain experts and software developers is essential to translate complex market and grid phenomena into reliable, scalable machine learning solutions.

Key Responsibilities

• Prepare and engineer features from raw data;
• Develop and train neural networks and other machine learning models;
• Evaluate and enhance model accuracy and performance;
• Integrate models into live production environments;
• Research and apply novel AI techniques;
• Participate in code reviews and maintain best practices in documentation;
• Ensure reliability, security, and robust performance of the platform.

Required Qualifications and Skills

• Solid grounding in Computer Science, including algorithm design supporting efficient and scalable implementations;
• Expertise in Pattern Recognition and Neural Networks for analyzing complex, multi-dimensional data;
• Strong statistical knowledge applied to experiment design, model assessment, and handling uncertainty;
• Practical experience with contemporary machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn, with proficiency in Python programming;
• Experience managing large datasets, data pipelines, and operating in cloud or distributed computing contexts;
• Possession of a Bachelor’s or Master’s degree in Computer Science, Data Science, Electrical Engineering, or a closely related quantitative discipline, or equivalent hands-on experience;
• Ability to work collaboratively across departments, clearly communicate complex technical details, and thoroughly document technical work;
• Interest or experience in energy sectors, including power markets or infrastructure planning, is highly valued.