Total 1,803 Senior Executive quality assurance engineer job vacancies in Australia

About this opportunity

The IT Infrastructure Engineer is responsible for designing, implementing, and maintaining the IT infrastructure within the manufacturing environment. This role ensures the stability, integrity, and efficient operation of the information systems that support manufacturing processes and business operations

Your key responsibilities will be to:

• Design and deploy functional networks (LAN, WLAN, WAN) tailored to manufacturing needs.
• Configure and install software, servers, routers, and other network devices.
• Monitor network performance and ensure system availability and reliability, particularly for manufacturing systems.
• Perform network maintenance and system upgrades including service packs, patches, hot fixes, and security configurations.
• Troubleshoot network issues and outages, minimizing downtime in manufacturing operations.
• Provide Level 2/3 support and troubleshooting to resolve issues.
• Liaise with vendors and other IT personnel for problem resolution.
• Ensure compliance with industry standards and regulations relevant to manufacturing.

Your skills and experience

To be successful in this role, you’ll have:

• Proven experience as a Network Administrator or similar role, preferably in a manufacturing environment.
• Deep understanding of network infrastructure and network hardware.
• In-depth knowledge of network management and monitoring tools.
• Experience in office relocations
• Experience with firewalls, VPN, and other security measures.
• Strong problem-solving and communication skills.
• Ability to work independently and as part of a team.
• Familiarity with manufacturing systems and processes is a plus.

As a result of a significant project pipeline, AECOM's Western Australian Resource and Industry Business Line has an opportunity for a Senior Mechanical Engineer to support the successful completion of projects across Western Australia, Australia and Globally.

Working as part of a dynamic, consulting environment, you will have the opportunity to work on a range of projects within Mining and associated Industries, such as surface, underground mine operations and within Iron Ore, Alumina, Gold, Manganese Ore etc.

Our team of industry experts and network of technical specialists will support the development of your technical and project management capabilities, giving you the opportunity to support project delivery to a broad range of clients and industry sectors. Working across mining, renewable energy, power and defence will give you a broad exposure and help build your career.  

What will a day in this role look like?

• Consulting with large Mining clients with a particular focus on mining infrastructure, materials handling and non-process infrastructure for brownfield and greenfield assets (specifically crushing, screening and bulk materials handling).
• As a Mechanical Engineer with AECOM you will provide Project Engineering and technical leadership for the project and studies.
• Act as focal point for the client, including interacting and building relationships with the clients.
• Use your experience as an Engineer to deliver technical outcomes for the project.
• The benefit of Perth based, with the opportunity to get involved in site based projects where you can visit (day trips) and work on site as required
• Agility in approaching workload, with the ability to move into projects at short notice and deliver high-quality work output.

About Us:

At Spinify, we're transforming how sales teams learn, grow, and succeed through cutting-edge AI-driven coaching and performance tools. We are on a mission to shift from gamification towards an intelligent coaching platform that leverages AI and real-time data to deliver personalized coaching, learning, and competition recommendations for sales teams. As we scale, we’re looking for an experienced AWS Machine Learning Engineer to help us build and maintain an innovative platform that ties coaching, learning, and AI together in a way that’s never been done before.

The Role:

We are seeking a Senior AWS Machine Learning Engineer who will be responsible for designing, developing, and deploying AI-powered solutions that personalize learning experiences, predict performance outcomes, and provide real-time coaching feedback. You will be working with a stack of cutting-edge AWS technologies to create an adaptive system that integrates real-time data, predictive analytics, and machine learning models.

Key Responsibilities:

• Build and deploy scalable Machine Learning models using AWS SageMaker for personalized learning, predictive analytics, and performance coaching.
• Develop and manage real-time data pipelines using AWS Kinesis and AWS Glue for streaming performance data, integrating third-party data sources, and ensuring accurate data flow.
• Design, implement, and optimize natural language querying using AWS Q to allow managers and users to interact with performance data and get actionable insights.
• Use Amazon Personalize to create dynamic, personalized learning paths and recommendations for users based on their performance and activity.
• Implement emotional intelligence analysis using Amazon Rekognition and Amazon Comprehend to analyze video coaching sessions and deliver AI-driven feedback on tone, sentiment, and body language.
• Build and maintain real-time dashboards using Amazon QuickSight for visualizing performance data, coaching progress, and competition standings.
• Create serverless workflows using AWS Lambda and API Gateway to automatically trigger coaching suggestions, performance alerts, and competition rule adjustments based on real-time data.
• Work with AWS Bedrock to integrate generative AI models for creating personalized quizzes, coaching strategies, and competition challenges.
• Ensure data privacy and security across all services, managing user access with AWS IAM and maintaining compliance with best practices (GDPR, SOC2, etc.).

Requirements:

• 5+ years of experience with AWS Cloud Services, particularly SageMaker, Kinesis, Glue, Lambda, Personalize, and QuickSight.
• Strong background in machine learning, including model training, optimization, and deployment using AWS SageMaker.
• Experience in building and managing real-time data pipelines using Kinesis and integrating large datasets using Glue or other ETL tools.
• Expertise in Natural Language Processing (NLP), with practical experience using Amazon Comprehend and Amazon Transcribe for sentiment and text analysis.
• Familiarity with AWS Bedrock and integrating generative AI models into real-world applications.
• Strong programming skills in Python and SQL.
• Experience with API development using API Gateway and Lambda for creating serverless, scalable APIs.
• Experience building real-time data visualizations and dashboards using Amazon QuickSight.
• Knowledge of data security best practices, including working with AWS IAM and compliance frameworks such as GDPR and SOC2.
• Strong analytical and problem-solving skills, with the ability to optimize performance and scale solutions.

Preferred Qualifications:

• Previous experience working in sales enablement or coaching platforms.
• Experience with DevOps tools such as CloudFormation or Terraform for automating infrastructure deployment and scaling.
• Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch) for advanced AI model building.

What We Offer:

• Competitive salary with performance-based bonuses.
• Remote work flexibility.
• Opportunity to work with cutting-edge AI and cloud technologies.
• A collaborative and innovative team environment.
• Opportunities for professional development and growth in the AI and ML space.