Senior Machine Learning Engineer

At AustralianSuper, we truly care about our colleagues. We know work and life are intertwined. That’s why we support the diverse needs of everyone and have policies that enable us all to thrive and be truly flexible. We ensure diversity is celebrated for the opportunity it provides us all to learn and grow, and deliver better outcomes for members.

Your New Role

The Senior Machine Learning Engineer is responsible for driving the strategic development of machine learning models that support our organisational goals and enhance our data-driven decision-making capabilities.

The role involves enabling Data Scientists and Data Analysts to deliver on high value prioritised use cases across the Fund (i.e. Operations, Investments, Member, Risk etc.) through high quality machine learning engineering and MLOps best practices.

This role will work closely with the Data Scientists and business stakeholders across the fund to:

• Deploy and automate the execution of models in production environments


• Develop, innovate and deliver advanced analytics (e.g. Predictive, Econometric and Optimisation models)


• Act as an incubator for advanced analytics with a focus on areas of lower maturity and/or high strategic value


• Support a Fund-wide process for analytics use case identification, prioritisation and planning


• Provide input and support for recommendations and prioritisation of data activities and initiatives for the Fund


• Support the development and maintenance of the Analytics Hub – the Fund’s implementation of Azure ML


• Support the development of a data science ‘Centre of Excellence’ which aides Business Units in the achievement of their analytics requirements (incl. knowledge sharing, upskilling, guidelines, support repositories etc.).

Key Responsibilities will include:

• Developing, deploying, and maintaining machine learning models using the Azure ML stack, ensuring scalability and efficiency


• Advancing the use of advanced analytics across the fund by enabling other teams to implement data science solutions


• Championing MLOps practices within the organisation, promoting frameworks that streamline model deployment and management


• Collaborating with cross-functional teams to integrate machine learning solutions into existing business processes


• Optimising ML workflows for performance and accuracy, leveraging Azure's suite of tools and services


• Leading technical discussions and providing mentorship to data and analytics colleagues across the Fund, fostering a culture of continuous learning and improvement


• Conducting thorough testing and validation of models to ensure robustness and reliability


• Staying abreast of the latest advancements in machine learning and Azure technologies, applying new techniques to enhance model performance


• Collaborating with IT teams to enhance the infrastructure, security and governance supporting machine learning operations


• Supporting the reporting on Key Performance Indicators and Metrics related to Advanced Analytics (e.g. effort invested, model benefit realisation, model uptake, handover success).

What You’ll Need

Essential:

• Proven experience in machine learning engineering, with strong proficiency in cloud-based environments such as Azure ML


• Previous experience implementing MLOps practices


• Strong track record in supporting the delivery of predictive, optimisation and econometric models that improve business outcomes and performance


• Strong understanding of experimental design and measuring uplift and causal impact


• Deep experience in productionising advanced analytical techniques (and when to use them)


• Advanced programming skills in Python


• Advanced SQL skills


• Advanced use of MS Office products: Excel, Word and PowerPoint


• Advanced written and oral communication/ interpersonal skills with the ability to present ideas, perspectives and issues to senior management


• Excellent problem solving, analytical and research skills, with a strong attention to detail


• High levels of initiative with the ability to deal with multiple projects simultaneously with conflicting priorities

Desired:

• Previous experience in Superannuation or other Financial Services


• A master's degree or higher in computer science, data science, or a related field


• Deep experience with cloud environments: MS Azure, AWS, GCP


• MS Azure certifications (Foundations etc)

Life at AustralianSuper

AustralianSuper is committed to colleague development, and we support our people with ongoing learning, coaching and training, as well as career opportunities across our expanding global organisation. We offer generous leave entitlements and promote a blended working environment in which all roles can flex, and we’re happy to discuss what this looks like for you.

We cultivate a workplace that champions safety, respect, inclusiveness and diversity.  We are committed to supporting our diverse workforce in a way that is inclusive and embraces diversity in all its forms. If you require any reasonable adjustments to the recruitment process or the role, please let our recruitment team know.

What’s Next

Apply now, if you share our values of Energy, Integrity, Generosity of Spirit and Excellent Outcomes and would like the opportunity to work in a challenging, growing and rapidly evolving team to deliver outstanding results.

Australian or New Zealand citizenship or Australian permanent residency status is required.

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Agencies please note: this vacancy is being managed directly by AustralianSuper’s Talent Acquisition team. We will contact our preferred agency partners should we require additional support. Thank you.