Machine Learning Engineer

2 days ago

Sydney, New South Wales, Australia beBeeDataScientist Full time $120,000 - $180,000

Job Title: Senior Data Scientist

Job Description:

Australian Energy Market Operator (AEMO) is Australia's independent energy system and market operator. Our purpose is to ensure safe, reliable and affordable energy today, and enable the energy transition for the benefit of all Australians.

We have the once-in-a-lifetime opportunity to co-design the future of our energy systems, and our core values revolve around character, commitment, and connection.

Our team's main focus are the engineering apps and real-time analytics tools that help us make sense of in-streaming data, by combining and visualising many different data sources intelligently.

The control rooms monitor and operate the electricity grids and gas grids 24/7.

With AI trending relentlessly, and the integration of renewables providing a steady stream of challenges to solve, there has never been a more exciting time to be working on this project.

Key Responsibilities:
  • Work on projects and initiatives, ranging from data preparation to full-scale machine learning solutions.
  • Design, build, train, compare, evaluate, deploy and document using state-of-the-art advancements.
  • Write robust Python code for novel machine learning use cases and match the most appropriate machine learning approaches to engineering problems.
  • Take ownership of sharable artifacts such as graph databases of electricity grid assets and instigate knowledge-sharing sessions with the Analytics User Group.
  • Shadow the PSA Technical Lead as second-in-command for ITIL Service Management processes like IT Change Management.
What We're Looking For:

Someone who has experience with the complexities of many ML projects and can proudly share their expertise.

Someone who stands their ground when faced with hairy maths and dense academic papers, because their curiosity and excitement to solve problems always wins out.

Someone who likes to collaborate, mentor, and exchange knowledge, and who is totally comfortable admitting when they don't know.

Many successful ML projects that are running in production.

Understanding graph data and time-series, and shaping them for ML models.

Deploying models, working with data pipelines, supporting production systems.

Wrangling hardware drivers and config to offload matrix computations to GPU / TPU / NPU.

At any stage a candidate may be asked to complete a data science challenge.

About This Job:

This role involves designing, building, training, comparing, evaluating, deploying and documenting machine learning solutions.

It requires strong problem-solving skills, attention to detail, and ability to work effectively in a team environment.

Candidates should be able to demonstrate their expertise in machine learning, data science, and software development.

They should also have excellent communication and interpersonal skills.

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