ai engineer lead at Mascot Creative
South Australia, New South Wales, Australia -
Full Time


Start Date

Immediate

Expiry Date

06 Jan, 27

Salary

60000.0

Posted On

08 Oct, 26

Experience

7 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Industry

Information Technology & Services

Description

Company Description Amplink Technologies develops the Amplink modelling platform, a proprietary software solution built by energy experts to capture market, grid, and integrated system dynamics. The platform combines extensive data repositories with industry-trained MarketBrain AI to deliver clear, accessible analytics for complex energy challenges. Amplink’s intuitive tools support data-driven planning and decision-making for governments, utilities, and investors. Designed for energy systems in transition, the platform helps stakeholders understand risks, opportunities, and long-term system behavior.

Role Description The Machine Learning Engineer – AI & Intelligent Systems role at Amplink Technologies is a full-time, on-site position based in Adelaide, SA. In this role, you will design, develop, and deploy machine learning models that power the MarketBrain AI and enhance the Amplink modelling platform. You will work closely with energy domain experts and software engineers to translate complex market and grid dynamics into robust, scalable algorithms. Day-to-day tasks include data preprocessing and feature engineering, building and training neural networks and other ML models, validating and optimizing model performance, and integrating models into production systems. You will also contribute to research on emerging AI methodologies, participate in code reviews, document technical work, and help maintain high standards of reliability, security, and performance across the platform.

Qualifications

  • Strong foundation in Computer Science and Algorithms, with experience implementing efficient, scalable solutions.
  • Proficiency in Pattern Recognition and Neural Networks for modeling complex, high-dimensional data.
  • Solid understanding of Statistics for experimental design, model evaluation, and uncertainty quantification.
  • Hands-on experience with modern machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and programming languages such as Python.
  • Experience working with large datasets, data pipelines, and cloud-based or distributed computing environments.
  • Bachelor’s or Master’s degree in Computer Science, Data Science, Electrical Engineering, or a related quantitative field, or equivalent practical experience.
  • Ability to collaborate with cross-functional teams, communicate complex technical concepts clearly, and document work thoroughly.
  • Background or strong interest in energy systems, power markets, or infrastructure planning is highly desirable.


Responsibilities
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