Senior Data Engineer, Machine Learning
Classification: ANU Officer 8 / Senior Manager 1
Salary package: $97,812 to $117,039
Terms: Full time, Fixed term (2 years)
- Be a part of the joint ANU and CSIRO Data61 team developing software which is applying cutting-edge machine learning research to large scale, real world problems involving large networks.
- Contribute to software solutions which are making a difference to previously unsolved problems experienced by key partner agencies in the Australian Government.
The ANU College of Engineering and Computer Science (CECS) is dedicated to contributing to The Australian National University’s reputation for excellence in research and research-led education, bringing together expertise across a range of areas to reimagine the role of engineering and computing for future generations. CECS is a diverse and vibrant community dedicated to discovery and to making knowledge matter. Our academics and students are engaged in ground-breaking, cutting-edge research, in exciting areas such as renewable energy, robotics, telecommunications, biomaterials, human-machine interaction, and artificial intelligence.
The Research School of Computer Science (RSCS) is unique in Australia. It includes a creative mix of staff and students that embrace the breadth of computer science profession. It is a diverse and vibrant community dedicated to discovery and to making knowledge matter. It contains world-class academics undertaking high-quality research, training of research students and delivering coursework teaching programs.
This position is a fixed term 2-year appointment (extendible based on performance) located in the Data Science for Public Good team at RSCS to work on the Integrated Graph Analytics Collaborative Research Project. The Integrated Graph Analytics Project is a joint undertaking of ANU RSCS and CSIRO's Data61 that is developing the Stellargraph platform for graph analytics, in partnership with key public-service agencies in the security domain.
Stellargraph uses new graph machine learning techniques from the graph learning research field to make predictions on complex problems in our highly connected world. Representing data as graphs enables the context and rich, relationship-driven structure of multiple data sources to be modelled to make predictions and reveal hidden insights in big data.
Applications are invited from data or software engineers with experience in developing software solutions to large scale, real world problems using machine learning. We are especially looking for a data engineer with expertise in one or more of machine learning, graph databases and sequential decision theory.
We welcome and develop diversity of backgrounds, experiences and ideas and encourage applications from individuals who may have had non-traditional career paths, who may have taken a career break or who have achieved excellence in careers outside of academia.
For further information please contact Associate Professor Kee Siong Ng
T: +61 (0)499 950 627,
Closing date: 5 May 2019
Position description: CECSProfessional-TechnicalOfficer-ResearchEngineer.pdf
ANU values diversity and inclusion and is committed to providing equal employment opportunities to those of all backgrounds and identities. For more information about staff equity at ANU, visit https://services.anu.edu.au/human-resources/respect-inclusion
The ANU provides attractive benefits and excellent support to maintain a healthy work/life balance and offers generous remuneration benefits, including four weeks paid vacation per year, assistance with relocation expenses and 17% employer contribution to superannuation. This also includes generous parental leave, the possibility of flexible and part time working arrangements, a parental and aged care support program, dual career hire programs, ANU school holiday programs, and childcare facilities on campus. For more information, please visit https://services.anu.edu.au/human-resources
Applicants must apply online via the ANU recruitment portal and should upload the following separate documents:
- A detailed curriculum vitae including a full publication list and the names and contact details of at least three referees (preferably including a current or previous supervisor). If your CV does not include referees you can complete these online when prompted in the application form.
- A statement addressing the selection criteria.
Please note: The successful applicant must have rights to live and work in this country.