Nearly 10% of all jobs in Australia are in the construction industry. Currently, there are more than 1.1 million construction staff and by May 2023 this number is set to increase another 10%. The industry, however, is not safe. Over five times more construction workers die than on site compared to Australian Defence Force casualties in Afghanistan, Iraq and East Timor. Sightdata is a Canberra-based start-up using our passion and knowledge in construction and machine learning to do.
There are four internship projects on offer from Sightdata.
Project 1: MLOps Engineer
This role is to support the transition of Sightdata’s technology from TRL7 (pilot) to TRL8 (production). This MLOps internship is a key role in the industrialisation phase of our product. If you are successful in this application, you can expect to work on ML pipeline design and optimisation including data versioning, warehousing, infrastructure and tooling for distributed training, ML experiment management, deployment, testing, monitoring and CI.
Within the highly specialist ML industry it is unusual to be presented an opportunity with end-to-end visibility of exactly how to go from ‘git clone’ to production AI. Although we have our own list of priorities students will be encouraged to explore their own value additions to the Sightdata MLOps pipeline. For the future big tech CEOs among you, this opportunity is an excellent experience in taking an ML product or service to market. To find out more about MLOps please see: https://cloud.google.com/architecture/mlops-continuous-delivery-and-automation-pipelines-in-machine-learning
Required technical skills
- At least one-year experience programming in Python.
- At least one deep learning course (at a university or online).
- Experience with code versioning, Unix environments, and software engineering.
- Basic experience with AWS is preferred.
- Personal GitHub repos or contributions to existing open-source repos would be ideal.
Required/preferred professional and other skills
Professional skills and personal qualities:
This project is aimed at students who are already comfortable with the basics of deep learning and want to understand the rest of the process of creating production systems. While we do not expect you to be Andrej Karpathy, we certainly hope the student brings a lot of passion to learn and grow.
Remote (Intern engages on project in a remote capacity)
Only students located within Australia
Project’s Special Requirements/ Conditions
Intern must be residing in Australia during the duration of the internship placement (the requirement amended by the Host - Sightdata for Round 2)
Type of internship
How to apply
Applications are invited from eligible students to apply for the Computing Internship courses COMP3280 or COMP8830. Eligibility details of COMP3280/ COMP8830 and further information about the Computing Internship can be found on the Computing Internship page.
- Eligible students can apply through the Computing Internship application form which will be available via the Computing Internship page between 10 May and 17 May. You can nominate multiple preferred Internship projects and host organisations through the one online application form.
- Eligibility and Room Available in degree to undertake COMP3280/COMP8830 will be assessed at the time of application. If you do not meet the eligibility criteria or do not have room in your degree to fit COMP3280/COMP8830, your application will not be progressed.
- Your application will require you to upload the following documents:
- an updated copy of your Resume, and
- an Expression of Interest (limit 350 words) for each organisation you wish to apply to (for organisations with multiple projects only submit one Expression of Interest but state clearly which project/s you wish to be considered for).
Round 2 Applications open on Tuesday 10 May 2022 and close on Tuesday 17 May 2022.