Job Description
Key Responsibilities
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Design and develop AI Design driven solutions that address strategic business needs and enhance enterprise capabilities.
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Transform existing business processes to be AI-first or AI-enabled, ensuring seamless integration with current systems.
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Collaborate with cross-functional teams to identify AI opportunities and create roadmaps for AI implementation.
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Design within industry standards User Experience, Security, Financial discipline and Responsible AI guidelines and frameworks.
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Develop and maintain AI models, ensuring their relevance and effectiveness in addressing business challenges.
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Implement model management and AI governance practices to ensure compliance, transparency, and ethical AI usage.
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Integrate AI solutions into enterprise systems and workflows, optimizing for performance and scalability.
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Conduct thorough testing and validation of AI models to ensure accuracy, reliability, and robustness.
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Model Development: Design, develop, and optimize AI and ML models to meet specific project needs.
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Data Analysis: Perform data collection, cleansing, and preprocessing to prepare robust datasets for modeling.
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Algorithm Selection: Assess and select appropriate algorithms and tools for model creation.
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Performance Evaluation: Evaluate model performance using relevant metrics and refine models as needed.
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Documentation: Maintain detailed documentation of model development processes, parameters, and outcomes.
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Collaboration:



Work closely with cross-functional teams to integrate AI solutions into business operations.
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Innovation: Stay updated with the latest advancements in AI and ML technologies and implement best practices.
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Technical Disciplines
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Data Science: Proficiency in data analysis, data mining, and data visualization techniques to extract valuable insights from large datasets.
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Modelling: Expertise in developing and deploying machine learning models, including supervised, unsupervised, and reinforcement learning techniques.
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Process Design: Ability to design and optimize business processes, ensuring they are aligned with AI capabilities and objectives.
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Model Management: Experience in model lifecycle management, including versioning, monitoring, and retraining of AI models.
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Model and AI Governance: Knowledge of best practices in AI governance, including ethical considerations, bias mitigation, and regulatory compliance.
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Required Skills and Competencies
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Data Science (DATS): Proficiency in data science techniques and methodologies to analyze complex datasets.
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Machine Learning (MLNG): Expertise in machine learning frameworks, libraries, and tools.
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Programming (PROG): Solid programming skills in languages such as Python, R, or Java.
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Analytics (INAN): Ability to derive insights from data through statistical and analytical methods.
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Algorithm Design (ALDS): Knowledge of algorithm design principles and their application in solving real-world problems.
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Business Analysis (BUAN): Understanding business requirements and translating them into technical solutions.
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Testing (TEST): Experience with model testing, validation, and quality assurance processes.
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Project Management (PRMG): Skills in managing AI/ML projects from conception to deployment.
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Qualifications
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Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
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3+ years of experience in designing and implementing AI and ML models.
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Strong problem-solving skills and a proactive approach to identifying solutions.
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Excellent communication skills to convey complex technical concepts to non-technical stakeholders.
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Experience with cloud platforms like AWS, Azure, or Google Cloud is a plus.
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📌 Ai & Data Design Engineer (New South Wales)
🏢 Tech Aalto
📍 New South Wales