Lead ML Engineer

Job Description

An ASX100 business part that is owned by Australian universities, IDP is a pioneer in international education services. Our core business lines include student placement to Australia, US, UK, Canada and New Zealand institutions, English-language testing and training.

We are on a mission to build the world's leading platform and connected community to guide students along their journey to achieve their lifelong learning and career aspirations.

As a co-owner of IELTS, we deliver the English test that is trusted by more governments, universities, and organisations than any other. We also operate English language teaching schools in South East Asia.

We are innovators, driven by the needs of our customers and deep data insights. Our 5,000 team members based around the world understand that our services change lives – not only of our customers, but their wider communities. IDP over its half a century’s business service provider has an enormous volume of data which is its core IP. IDP operates in 33 countries for Student placement and in 60 countries for IELTS. Our websites have over 100 million visitors a year and have the World’s most comprehensive course and institution search across 40+ sites.

By combining empathy and professional expertise with digital excellence, we create launch pads for our customers to achieve global success.

You’ll spend time on the following:

In this role you will be collaborating with IDP’s Data Engineering and Governance, an enterprise capability team and be responsible for: -

• Design the data pipelines and engineering infrastructure to support our technology enterprise machine learning systems at scale
• Take offline models data scientists build and turn them into a real machine learning production system
• Develop and deploy scalable tools and services for our business to handle machine learning training and inference
• Maintain the infrastructure and tools that allow us to deploy and monitor our ML algorithms in production
• Identify and evaluate new technologies to improve performance, maintainability, and reliability of our business machine learning systems
• Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
• Support model development, with an emphasis on auditability, versioning, and data security
• Facilitate the development and deployment of proof-of-concept machine learning systems
• Communicate with business to build requirements and track progress with appropriate tools
• Define & implement our ML Ops strategy
• Work with our Data science team to deploy models in a performant and optimize ML models
• Monitor & maintain our ML systems in production
• Set up a robust experiment tracking infrastructure
• Work with Product owners, Data Scientist, Data Engineers, Data Analyst, Software developers incl. Architects to efficiently integrate our ML models into our wider technology stack
• Contribute to keeping Standards and best practices up to date collaborating with the community
• Promote the best practices and correct usage of standards
• Identify areas in need of improvement and the drive to put a solution in place which addresses those needs
• Manage and prioritize multiple initiatives, incidents and service requests while adapting to changing business conditions
• Document standard operating procedures for repeatable tasks and contribute to automation efforts
• Prepare and maintain training material and SOPs, knowledge base articles and technical documentation

Take responsibility for Outcomes

You love technology, are continuously learning and extending your knowledge of best practice and the business value of technology innovations.

Here’s what we’re looking for:

• Bachelor’s degree in Computer Science / Statistics
• 5 -8 years+ experience of machine-learning in production with evidence of successful delivery and overall, 10+ years IT experience.
• Hand on experience with Quantitative analysis
• Experience with the full life cycle of ML projects, with a focus on deployment, monitoring and maintaining of ML systems along with quality assurance
• Should be able to validate models via back testing
• Should be able to design and develop time series algorithms and recommendation engines to bolster the product development organisation
• Ability to write robust code using python/ R
• Extensive knowledge on data structures and models
• Hands on experience with machine learning frameworks, libraries and deep learning
• Knowledge on Continuous integration and deployment
• Expertise in visualizing and manipulating big datasets
• Ability to translate business needs to technical requirements
• Able to effectively present information, gain feedback and respond to questions from groups of senior leaders, stakeholders, and customers
• Comfortable with working with multiple stakeholders in a multi-cultural environment
• Any ML Engineer certification is desirable

WORKING AT IDP

IDP Education’s ongoing success comes from our highly committed and caring employees around the globe. We encourage teamwork in order to leverage our people's diverse talents and expertise through effective collaboration and cooperation throughout our business.
We strive to provide a working environment where people are encouraged to excel, be creative, and seek new ways to solve problems, take initiative, generate opportunities, and be accountable for their actions.

We believe in developing dynamic, inclusive workplaces that encourage and celebrate cultural differences and views, and provide opportunities for personal, professional and career development all around the world. We respect diversity in our people: their ideas, work styles and perspectives as well as offering flexibility to ensure employees enjoy a satisfying balance of work and personal life.