Control Systems Senior Engineer

Fortescue Metals Group; Perth; On-site; AUD 150,000 - 210,000; Full time

Job summary

Fortescue Metals Group in Perth is seeking an experienced APC professional to design, build, deploy and support advanced process control systems for our fixed plant operations, including model predictive control with AI soft sensors and setpoint recommendations.

You will work in a forward-deployed AI delivery team, collaborate with data scientists, ML engineers and operations to deliver measurable improvements in operating rate, recovery, energy efficiency and water use.

Qualifications

• 5+ years of APC, industrial control or applied research.
• Tertiary qualifications in process engineering or related field.
• Ability to translate complex technical issues into clear requirements.
• Experience and interest in AI-enabled workflows.
• Practical experience in Python is well regarded.
• Familiarity with applied statistics and machine learning in industrial process operations is well regarded.

Responsibilities

• Owning the design, build, deployment and support of advanced process control systems across the development lifecycle.
• Helping identify, quantify and validate efficiency and opportunities, using data from a range of sources.
• Collaborating with other specialists (including data scientists and ML engineers) to develop and extend control schemes using AI methods.
• Collaborating with SMEs and users to shape technical requirements.
• Working closely with front-line and operational support teams to test, validate and refine models to support adoption and operational impact.
• Maintaining the backlogs for development, and collaborating with cross-functional teams to prioritise development.
• Supporting community development through technical engagement and leadership on advanced process control.

Skills

APC / advanced process control

Python

AI-enabled workflows

Data analysis

Industrial automation

Education

Bachelor's or higher in process/control engineering

Tools

Python

Job description

Work Location: Perth, CBD. Fortescue's Perth office is located on the traditional lands of the Whadjuk people.

Roster: Monday to Friday.

Reporting to: Principal Delivery Lead – Plant Control Intelligence

Fortescue is transforming its business through Artificial Intelligence, bringing our unique culture of innovation and leading through doing to transform our asset and employee productivity. In this role you will deliver advanced process control solutions for our fixed plant operations, extending advanced control schemes including model predictive control with AI soft sensors and setpoint recommendation models, to deliver measurable improvements in key performance drivers including operating rate, recovery & yield, energy efficiency and water use.

This role is suited to experienced individual contributors who deliver autonomously across remote and site teams. It would suit candidates coming from a range of backgrounds, including process & control engineering, industrial automation, or applied research. Experience in mineral processing & bulk materials handling control systems is valuable, particularly site experience, but we will also consider strong control specialists from other process industries. Regardless of background, you will bring a strong ability to analyse dynamic operational performance, define advanced control schemes that will be practical in real operations, and have the grit to lead the development, deployment and refinement of these.

You will work in a forward-deployed AI delivery team, with a focus on accelerated development of new solutions in multi-disciplinary teams, in close partnership with operations. As part of an AI delivery team, you would embrace the use of modern AI methods & tools (i.e. LLMs) and contribute to improvements to ways of working for process control workflows.

Key Responsibilities

• Owning the design, build, deployment and support of advanced process control systems across the development lifecycle
• Helping identify, quantify and validate efficiency and opportunities, using data from a range of sources
• Collaborating with other specialists (including data scientists and ML engineers) to develop and extend control schemes using AI methods
• Collaborating with SMEs and users to shape technical requirements
• Working closely with front-line and operational support teams to test, validate and refine models to support adoption and operational impact
• Maintaining the backlogs for development, and collaborating with cross-functional teams to prioritise development
• Supporting community development through technical engagement and leadership on advanced process control

Qualifications and Experience

• 5+ years of experience in APC, industrial control or applied research, with strong foundations and practical experience in model-based control
• Tertiary qualifications in process engineering, control engineering or a related field, or equivalent experience
• Ability to translate complex technical issues into clear requirements
• Experience and interest in AI-enabled workflows
• Practical experience in Python is well regarded
• Familiarity with applied statistics and machine learning in industrial process operations is well regarded

About Us

Be part of something big. Fortescue is leading the world with our plan to decarbonise our iron ore operations, projects that harness renewable energy and the development of technology that will change our planet forever.

Our Commitment

Fortescue celebrates individual strengths and team members are encouraged to bring their whole selves to work. Our global workforce drives and promotes an inclusive culture, both within our organisation and throughout the communities we interact with. Diverse backgrounds include First Nations Peoples, people with disabilities, LGBTQ+ community, gender, neurodiverse, cultural diversity, all age groups, and those with an intersectional or multiple diverse characteristics. We encourage candidates from all backgrounds to apply.

Fortescue reserves the right to close applications early should a suitable pool of candidates be identified.