Machine Learning Operations Engineer
Machine Learning Operations Engineer - Brisbane
About the role
We have an opportunity for a Machine Learning Operations Engineer to support challenging and exciting analytics problems and make a positive impact to the business, while engaging with a global team of technology experts and engineers.
Reporting to the Manager Solution Advisory you will support the PACE Analytics team and newly create Analytics Centre of Excellence (CoE) to design and continually improve analytics solutions that solve business problems and provide insight to making improved decisions through:
You will also:
About you
We're looking for people that have a background in software development and experience on stacks similar to ours, with portfolio or qualifications to match. If you're bringing a Github repo full of interesting things, a killer portfolio, or a strong academic background: reach out. We realise every candidate has their own strengths and areas they want to grow, and we aim to support this in the team we're bringing together.
Our Stack
On the Front End: We use a mix of established and emerging tools, experimenting with what works. We use the technology that works for our customers, whether that is Plotly's Dash, RStudio Connect, Shiny, and Tableau or React, Angular or Vue.js.
For Machine Learning: We use Azure ML and AWS Sagemaker. We have also experimented with AWS EMR, Azure Databricks, and with serverless architectures such-as Azure Synapse, Azure functions, AWS Step functions and Lambda for both featuring engineering and model inference. We also support RStudio for our resident data scientists across the group.
On the Back End: Our engineers will talk about: Python (Numpy, Pandas, Dask, PyTorch, PySpark), SQL and R in Azure and AWS, leveraging services such as Data Factory, PostgresDB, RDS, EC2, Docker on ECS and Fargate, Lambda, Athena, Glue, and S3.
The role's focus is on the automation of infrastructure for our data science teams, through ARM and Cloudformation templates, and we are building machine learning operations capabilities leveraging tech such as Azure Devops, Github and Github Actions, Terraform, Jfrog, and Ansible.
Soft skills
Where you will be working
PACE Analytics is a Data Science and Optimisation team within Rio Tinto with a presence in our Brisbane, Perth, Singapore and Montreal hubs. Our mandate is to use the latest technologies to build ML and AI products to help maximise the value of our operations. We use a combination of open source and cloud native technologies to build our solutions, across a diverse group of Data Scientists, Software Engineers and Delivery Experts from a range of industry and academic backgrounds.
About Rio Tinto
Every idea, every innovation, every little thing the world calls 'progress' begins with a first step, and someone willing to take it: explorers, inventors, entrepreneurs. Pioneers.
For nearly 150 years, Rio Tinto has been a company of pioneers generations of people spanning the globe, all with the grit and vision to produce materials essential to human progress.
Our iron ore has shaped skylines from Shanghai to Sydney. Our aluminium the world's first to be certified "responsible" helps planes fly and makes cars lighter. Our copper helps wind turbines power cities and our boron helps feed the world, and explore the universe.
Our diamonds help us celebrate the best parts of life.
Every Voice Matters
At Rio Tinto, we particularly welcome and encourage applications from Aboriginal and Torres Strait Islander people, women, the LGBTI+ community, mature workers, people with disabilities and people from different cultural backgrounds.
We are committed to an inclusive environment where people feel comfortable to be themselves. We want our people to feel that all voices are heard, all cultures respected and that a variety of perspectives are not only welcome they are essential to our success. We treat each other fairly and with dignity regardless of race, gender, nationality, ethnic origin, religion, age, sexual orientation or anything else that makes us different.
- Diverse and challenging projects within PACE Analytics
- Build innovative solutions to help data science and data engineering teams move faster
- Work in a flexible work environment where we champion engagement and diversity
About the role
We have an opportunity for a Machine Learning Operations Engineer to support challenging and exciting analytics problems and make a positive impact to the business, while engaging with a global team of technology experts and engineers.
Reporting to the Manager Solution Advisory you will support the PACE Analytics team and newly create Analytics Centre of Excellence (CoE) to design and continually improve analytics solutions that solve business problems and provide insight to making improved decisions through:
- Utilising the latest available cloud technologies to flexibly manage and scale machine learning pipelines and analytics models
- Designing, building, and deploying complex compute and storage environments and machine learning pipelines to serve analytics solutions
- Supporting data science and data engineering teams with cloud automation solutions
- Challenging and collaborating to derive new and novel techniques to improve the team processes and techniques
- Developing Machine Learning (ML) platforms and processes that support delivery and the operations for ML solutions.
You will also:
- Ensure best in class processes and techniques to develop and deploy cloud solutions to the business
- Capture and record the intellectual property generated and help promote best practices and patterns.
- Provide upskilling and knowledge transfer to support the deployment and continuity of the analytics products developed
About you
We're looking for people that have a background in software development and experience on stacks similar to ours, with portfolio or qualifications to match. If you're bringing a Github repo full of interesting things, a killer portfolio, or a strong academic background: reach out. We realise every candidate has their own strengths and areas they want to grow, and we aim to support this in the team we're bringing together.
Our Stack
On the Front End: We use a mix of established and emerging tools, experimenting with what works. We use the technology that works for our customers, whether that is Plotly's Dash, RStudio Connect, Shiny, and Tableau or React, Angular or Vue.js.
For Machine Learning: We use Azure ML and AWS Sagemaker. We have also experimented with AWS EMR, Azure Databricks, and with serverless architectures such-as Azure Synapse, Azure functions, AWS Step functions and Lambda for both featuring engineering and model inference. We also support RStudio for our resident data scientists across the group.
On the Back End: Our engineers will talk about: Python (Numpy, Pandas, Dask, PyTorch, PySpark), SQL and R in Azure and AWS, leveraging services such as Data Factory, PostgresDB, RDS, EC2, Docker on ECS and Fargate, Lambda, Athena, Glue, and S3.
The role's focus is on the automation of infrastructure for our data science teams, through ARM and Cloudformation templates, and we are building machine learning operations capabilities leveraging tech such as Azure Devops, Github and Github Actions, Terraform, Jfrog, and Ansible.
Soft skills
- Engage with clients and key stakeholders (IST) to build their understanding of cloud, machine learning operation and cloud automation.
- Drive change by fostering an innovative and "disruptive" technology culture to identify and drive value creating opportunities
- Help the broader PACE team and clients prioritize by advising technical complexity of identified opportunities
- Familiar with Agile delivery and project management
Where you will be working
PACE Analytics is a Data Science and Optimisation team within Rio Tinto with a presence in our Brisbane, Perth, Singapore and Montreal hubs. Our mandate is to use the latest technologies to build ML and AI products to help maximise the value of our operations. We use a combination of open source and cloud native technologies to build our solutions, across a diverse group of Data Scientists, Software Engineers and Delivery Experts from a range of industry and academic backgrounds.
About Rio Tinto
Every idea, every innovation, every little thing the world calls 'progress' begins with a first step, and someone willing to take it: explorers, inventors, entrepreneurs. Pioneers.
For nearly 150 years, Rio Tinto has been a company of pioneers generations of people spanning the globe, all with the grit and vision to produce materials essential to human progress.
Our iron ore has shaped skylines from Shanghai to Sydney. Our aluminium the world's first to be certified "responsible" helps planes fly and makes cars lighter. Our copper helps wind turbines power cities and our boron helps feed the world, and explore the universe.
Our diamonds help us celebrate the best parts of life.
Every Voice Matters
At Rio Tinto, we particularly welcome and encourage applications from Aboriginal and Torres Strait Islander people, women, the LGBTI+ community, mature workers, people with disabilities and people from different cultural backgrounds.
We are committed to an inclusive environment where people feel comfortable to be themselves. We want our people to feel that all voices are heard, all cultures respected and that a variety of perspectives are not only welcome they are essential to our success. We treat each other fairly and with dignity regardless of race, gender, nationality, ethnic origin, religion, age, sexual orientation or anything else that makes us different.