Job Title: CSIRO Postdoctoral Fellowship in Aquaculture Genetics Company: CSIRO Job Category: Machine Learning Roles & Responsibilities: Role highlights * Advance aquaculture breeding through genetics, genomics and data science * Develop innovative tools to guide breeding decisions across generations * Collaborate on supporting a resilient, sustainable aquaculture industry The opportunity CSIRO Early Research Career (CERC) Fellowships provide opportunities to scientists and engineers who have completed their doctorate and have less than three years relevant research experience. These Fellowships aim to develop the next generation of future leaders of the innovation system. Help shape the next generation of aquaculture breeding. In this postdoctoral role, you’ll combine quantitative genetics, genomics, optimisation and data science to develop breeding strategies for high\-performing, resilient and adaptable populations across future generations and diverse production environments. Your research will integrate multi\-objective optimisation, Look\-Ahead Genomic Selection, genotype\-by\-environment\-by\-management modelling and haplotype stacking to guide selection and mating decisions. Working with a collaborative, multidisciplinary team, you’ll translate your research into practical decision\-support tools that help breeders balance genetic gain, resilience, adaptability, sustainability and genetic diversity. With scientific, technical and industry support, you’ll develop new ideas, build your research capabilities and deliver outcomes with practical value for the aquaculture industry. Your high\-level duties will include: * Develop and evaluate next\-generation quantitative genetic and genomic methods for aquaculture breeding, including multi\-trait, multi\-environment and G×E×M prediction. * Develop multi\-objective breeding optimisation approaches that balance genetic gain, resilience, sustainability, profitability and genetic diversity. * Develop and test Look\-Ahead Genomic Selection and haplotype\-stacking approaches to improve long\-term breeding outcomes across generations. * Build simulation and optimisation frameworks to evaluate breeding strategies under changing environmental, disease, management and production scenarios. * Integrate genomic prediction, optimisation, mate allocation and look\-ahead decision methods into practical breeding decision\-support tools. * Validate the methods using simulated and real aquaculture datasets and assess their transferability across species and production systems. * Develop reproducible research software, computational pipelines and technical documentation. * Publish and communicate research findings, contribute to collaborative research and industry engagement, and support future research and funding opportunities. Role particulars Tenure \& work schedule: Specified term of 3 years, Full\-time Please note: To be eligible for this role you must have no more than 3 years (or full\-time equivalent) of relevant research experience. * Strong knowledge of quantitative genetics and/or genomic prediction. * Demonstrated expertise in statistical modelling and computational analysis. * Strong programming skills in at least one scientific programming environment such as R, Python or C\+\+. * Experience analysing large genetic, genomic or biological datasets. * Develop novel algorithms for multi\-stage and long\-term breeding decision optimisation. * Design and implement scalable computational methods capable of analysing large genomic and phenotypic datasets. * Apply advanced statistical learning, machine learning and artificial intelligence approaches where appropriate to improve prediction and decision\-making performance. * Develop efficient software implementations using modern programming practices, parallel computing and reproducible research workflows. * Evaluate optimisation and prediction methods under uncertainty using simulation\-based experimentation and sensitivity analysis. * A record of high\-quality scientific publication appropriate to career stage. * Demonstrated ability to work effectively within collaborative and multidisciplinary research teams. * Strong scientific writing, communication and organisational skills. For full details about this role, please review the Position Description. Setting you up for success We are committed to providing a recruitment process that is fair, equitable and accessible to everyone. We recognise that it may be helpful for us to adjust our process to make it equitable for your individual situation. Please contact Laura Mason via Careers.Online@csiro.au and let us know how we can support you. How to apply Please apply online and submit a CV and cover letter (maximum 2 pages) that demonstrate your motivation and ability to meet the selection criteria of this role. Work Location: Hobart, Australia Availability: Full time
Job Title: Senior Manager, AI Engineering Company: H2O.ai Job Category: Machine Learning Roles & Responsibilities: H2O.ai is on a mission to democratize AI for Good. As the world’s leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose\-built Agents, SLMs, and solutions on their private data. With a focus on secure, compliant, and infrastructure\-flexible Sovereign AI deployments, H2O.ai delivers solutions that align with the highest standards of data privacy and control. We are looking for a Senior Manager, AI Engineering who builds things that matter. You will design and ship end\-to\-end AI solutions for some of APAC's most complex enterprise problems \- spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands\-on engineering role embedded within a customer\-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one. What You Will Do * Lead end\-to\-end delivery of AI/ML and GenAI solutions for enterprise customers across industries such as financial services. * Own delivery execution across multiple concurrent AI workstreams, ensuring scope, timelines, quality and business outcomes are met. * Manage, mentor and grow a team of AI engineers and data scientists, owning hiring, onboarding, performance management and career development. * Own staffing and capacity planning across engagements, matching skills to accounts and clearing blockers for the team. * Manage technical delivery risks, dependencies and coordination across engineering, data science, product and customer teams. * Partner with customers to translate business problems into technical AI solutions, including model design, architecture and deployment approach. * Stay hands\-on: prototype, review and debug code, and make and defend architecture decisions. * Guide design and review of ML models (predictive ML, time series, classification, clustering) and GenAI systems (LLMs, SLMs, RAG, prompt engineering, evaluation, agentic workflows). * Ensure best practices across the ML lifecycle: data preparation, feature engineering, training, evaluation, deployment, monitoring and governance. * Raise the technical bar across the team through design and code reviews, pairing and structured feedback. * Act as the primary technical point of contact and escalation point for customers, balancing delivery execution with stakeholder management from engineer to executive level. * Partner with sales and pre\-sales on scoping, estimation, statements of work and expansion opportunities. * Collaborate with product and engineering teams to build reusable accelerators and reference architectures, and feed field learnings back into the roadmap. What We Are Looking For* 8\+ years in data science, machine learning, AI engineering or software engineering, with enterprise delivery experience. * 2\+ years leading technical teams, either through direct people management or sustained tech\-lead ownership of engineers and outcomes. * Demonstrated experience hiring, mentoring, giving performance feedback and developing engineers. * Track record of running multiple concurrent enterprise engagements to time, quality and budget. * Strong hands\-on foundation in predictive machine learning, including feature engineering, model development, evaluation and interpretability. * Experience building and deploying production AI systems, including APIs, backend services or ML\-powered applications. * Solid understanding of GenAI systems including LLMs, SLMs, RAG, prompt engineering, evaluation and agentic workflows. * Strong Python skills and production engineering practices (testing, CI/CD, debugging, version control, system design). * Experience with cloud platforms and MLOps/LLMOps concepts (deployment, monitoring, governance). * Ability to review technical implementations and guide architecture decisions, and to coach engineers to make those decisions independently. * Strong customer\-facing communication skills, comfortable moving between whiteboarding with engineers and presenting to executive stakeholders. * Experience with H2O products (Driverless AI, H2O\-3, H2O Wave, h2oGPTe, H2O LLM Studio). * Prior experience in technical consulting, solutions engineering, or AI delivery roles. * Experience building or scaling a technical team or function, not just inheriting one. * Experience managing distributed teams across time zones. * Commercial exposure: scoping, SOWs, estimation, and accountability for delivery margin. * Experience leading workshops, hackathons, or enterprise AI enablement programmes. * Exposure to regulated industries (financial services, healthcare, insurance). * Experience designing or reviewing full\-stack AI applications or platforms. * Contributions to Kaggle, open source, technical writing, or conference speaking. * Market leader in total rewards * Remote\-friendly culture * Flexible working environment * Be part of a world\-class team * Career growth H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting\-edge technology across a variety of industries. We’ve made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. Work Location: Sydney, NSW, Australia Availability: Full time
Job Title: Data Architect – Azure Data Platform & AI Company: Cognizant Job Category: Machine Learning Roles & Responsibilities: At Cognizant, together with your colleagues from all around the world, you will collaborate on creating solutions for the world’s leading companies and help them become more flexible, more innovative, and successful. Moreover, this is your chance to be part of the success story. We are seeking an experienced Data Architect with deep expertise in Azure Data Engineering, Microsoft Fabric, Databricks, PySpark, ETL/ELT development, Data Modeling, Data Warehousing, AI/Generative AI, and cloud\-based analytics platforms. The ideal candidate will be responsible for defining and implementing enterprise data architecture, designing scalable and reusable data models, and delivering modern data solutions that support analytics, reporting, machine learning, and AI\-driven initiatives. The role requires hands\-on experience in designing, building, optimizing, and supporting scalable data solutions across batch, streaming, API\-based, and file\-based ingestion frameworks. The candidate should possess strong knowledge of conceptual, logical, and physical data modeling, dimensional modeling, star and snowflake schemas, data governance, master data management, and enterprise data integration patterns. The successful candidate will be responsible for delivering reliable, secure, scalable, and high\-performing data pipelines while collaborating with business stakeholders, solution architects, and cross\-functional delivery teams in Agile and Waterfall environments. The role also includes driving data strategy, ensuring data quality, performance optimization, security, governance compliance, and enabling advanced analytics and AI capabilities across modern cloud\-based data ecosystems. * Proven hands\-on experience in designing, architecting, developing, and delivering enterprise\-scale data engineering, analytics, and AI\-powered solutions using Microsoft Fabric, Azure Databricks, Databricks SQL, Databricks Workflows, PySpark, and cloud\-native technologies across complex business environments. * Strong expertise in designing and implementing scalable data architectures, distributed data pipelines, ETL/ELT frameworks, real\-time and batch processing solutions, and high\-performance analytics platforms leveraging modern cloud ecosystems. * Extensive experience with Microsoft Fabric (OneLake, Lakehouse, Data Factory, Data Warehouse, Real\-Time Analytics, and Power BI) and Azure Databricks, including Unity Catalog, Delta Live Tables (DLT), Delta Lake, and Azure Data Lake Storage (ADLS) for secure, governed, and reliable data management. * Demonstrated capability in architecting and implementing enterprise\-scale Lakehouse and Data Mesh solutions, ensuring data quality, governance, lineage, security, compliance, and operational excellence. * Strong expertise in data modeling, including conceptual, logical, and physical data models, dimensional modeling, star and snowflake schemas, data vault modeling, and semantic layer design to support analytics and business intelligence requirements. * Proficiency in Python, PySpark, SQL, and Spark\-based frameworks for developing robust, optimized, reusable, and scalable data processing and analytical workloads. * Experience in designing and implementing AI/Generative AI solutions, including Azure OpenAI, Azure AI Services, Retrieval\-Augmented Generation (RAG), vector databases, AI\-powered analytics, and enterprise Copilot integrations. * Strong experience with Azure DevOps, CI/CD pipelines, Infrastructure as Code (IaC), release management, version control, and Agile delivery methodologies to support continuous integration and deployment practices. * Deep understanding of data architecture principles, cloud architecture patterns, performance optimization techniques, security frameworks, governance models, and cloud\-native solution design for large\-scale enterprise data ecosystems. * Experience in requirements analysis, solution architecture, effort estimation, resource planning, proposal preparation, technical leadership, stakeholder management, and delivery governance for data modernization and digital transformation initiatives. * Strong exposure to Agile ways of working, including Sprint Planning, Backlog Grooming, PI Planning, SAFe practices, Retrospectives, and cross\-functional collaboration across distributed teams. * Excellent communication, presentation, consulting, and leadership skills with the ability to influence strategic decisions, establish trusted client relationships, define data strategy and roadmaps, and drive customer\-centric business outcomes. * Experience in defining and implementing data governance, metadata management, master data management (MDM), data quality frameworks, and enterprise data standards to support regulatory and business requirements. Roles And Responsibilities: * Collaborate with business stakeholders, solution architects, AI specialists, and development teams to gather, analyze, and translate complex business requirements into scalable data, analytics, and AI\-driven platform solutions. * Lead end\-to\-end delivery of enterprise Data Warehouse, Data Lake, Lakehouse, Analytics, and AI initiatives using Microsoft Fabric, Azure Data Factory, Azure Databricks, Azure Synapse, Azure Data Lake Storage Gen2, and Azure AI Services. * Design and implement robust ETL/ELT frameworks for batch, streaming, API\-based, and file\-based data ingestion using Microsoft Fabric Data Factory, Python, PySpark, Event Hub, Databricks, and cloud\-native integration services. * Perform source system analysis, data profiling, data discovery, and data mapping activities to ensure accurate, secure, and efficient migration and integration of business\-critical data assets. * Develop and optimize data pipelines, transformation frameworks, semantic models, and analytical solutions to improve performance, scalability, and operational efficiency across enterprise data platforms. * Establish and enforce data quality, validation, governance, metadata management, and lineage standards by implementing automated monitoring, reconciliation, and compliance controls across data ecosystems. * Lead the design and implementation of Lakehouse architectures, enterprise data models, and AI\-ready data foundations to support advanced analytics, machine learning, and Generative AI use cases. * Design, develop, and integrate AI/Generative AI solutions, including Azure OpenAI, Retrieval\-Augmented Generation (RAG), vector search, AI\-powered analytics, and enterprise Copilot capabilities, leveraging governed enterprise data assets. * Lead technical teams across multiple projects, providing guidance on architecture, data modeling, AI integration, design patterns, coding standards, performance tuning, security, and cloud best practices. * Manage the complete project delivery lifecycle, including requirements gathering, solution architecture, estimation, sprint planning, development, testing, deployment, production support, and continuous improvement initiatives. * Drive Agile delivery practices through sprint planning, backlog refinement, status reporting, dependency management, risk mitigation, and stakeholder communication using Azure DevOps, Jira, and Microsoft Fabric monitoring capabilities. * Work closely with business users, data stewards, data owners, and cross\-functional teams to resolve data\-related issues and ensure successful implementation of business and AI requirements. * Design and implement conceptual, logical, and physical data models, including dimensional models, Fact and Dimension tables, Data Vault structures, and semantic layers, leveraging industry\-standard methodologies such as SCD Type 1 and Type 2\. * Architect and implement Microsoft Fabric solutions, including OneLake, Lakehouse, Data Warehouse, Data Factory, Real\-Time Analytics, and Power BI, to deliver unified and scalable enterprise analytics platforms. * Facilitate customer engagements, AI strategy workshops, technical design sessions, solution walkthroughs, and architecture reviews to align business objectives, data strategy, and AI transformation roadmaps with technical deliverables. * Define and promote enterprise data governance, security, privacy, and compliance standards while enabling self\-service analytics, trusted data products, and AI innovation across the organization. Work Location: Brisbane, QLD, Australia Availability: Full time
Job Title: AI Engineer - Senior Consultant Company: EY Job Category: Machine Learning Roles & Responsibilities: Working within the innovation team in our Digital Assurance practice, you’ll help move AI opportunities from discovery and feasibility assessment through rapid prototyping and into secure, scalable production delivery. This is a hands\-on engineering role rather than a pure research, strategy or architecture position. At Senior Consultant level, you’ll take ownership of defined technical workstreams and collaborate with senior technical, risk, product and engagement leaders. This is a hybrid position that can be performed from any of our EY offices across Australia. Our roles can potentially be adjusted to work flexibly with reduced hours. Please speak with us about potential options. Your Key Responsibilities * Design, develop, test and deploy AI\-enabled applications using Python and Microsoft Azure, including machine learning, generative AI and agentic AI solutions. * Translate business requirements and discovery findings into practical technical designs, prototypes and secure, production\-ready solutions. * Build scalable data, training and inference pipelines, applying source control, automated testing, CI/CD, monitoring and appropriate software engineering, security and operational practices. * Strong Python development skills and experience building production\-quality AI applications. * Practical experience with Azure AI services, including Azure AI Foundry, Azure OpenAI, Azure Machine Learning and Azure Databricks. * Experience delivering scalable AI pipelines using cloud\-native architecture, automated testing, CI/CD and MLOps practices. * Sound understanding of enterprise cloud security, monitoring and operational requirements. * Strong problem\-solving and communication skills, with the ability to translate business needs, contribute to solution design and own technical deliverables. Work Location: Brisbane, Queensland, Australia Availability: Full time
Job Title: AI Engineer - Senior Consultant Company: EY Job Category: Machine Learning Roles & Responsibilities: Working within the innovation team in our Digital Assurance practice, you’ll help move AI opportunities from discovery and feasibility assessment through rapid prototyping and into secure, scalable production delivery. This is a hands\-on engineering role rather than a pure research, strategy or architecture position. At Senior Consultant level, you’ll take ownership of defined technical workstreams and collaborate with senior technical, risk, product and engagement leaders. This is a hybrid position that can be performed from any of our EY offices across Australia. Our roles can potentially be adjusted to work flexibly with reduced hours. Please speak with us about potential options. Your Key Responsibilities * Design, develop, test and deploy AI\-enabled applications using Python and Microsoft Azure, including machine learning, generative AI and agentic AI solutions. * Translate business requirements and discovery findings into practical technical designs, prototypes and secure, production\-ready solutions. * Build scalable data, training and inference pipelines, applying source control, automated testing, CI/CD, monitoring and appropriate software engineering, security and operational practices. * Strong Python development skills and experience building production\-quality AI applications. * Practical experience with Azure AI services, including Azure AI Foundry, Azure OpenAI, Azure Machine Learning and Azure Databricks. * Experience delivering scalable AI pipelines using cloud\-native architecture, automated testing, CI/CD and MLOps practices. * Sound understanding of enterprise cloud security, monitoring and operational requirements. * Strong problem\-solving and communication skills, with the ability to translate business needs, contribute to solution design and own technical deliverables. Work Location: Perth, Western Australia, Australia Availability: Full time
Job Title: Clinical AI Engineer Company: Heidi Job Category: Machine Learning Roles & Responsibilities: We're building the future of healthcare by giving every clinician the earth's finest AI Care Partner. Our platform has absorbed the administrative chaos of 175 million patient visits and supported 67 million clinical hours. Today, we support 2\.8 million patient sessions a week across 190\+ countries, in 110 languages and over 200 specialties. The role ------------ * Design the evaluation. Define evaluations for greenfield products to an academic standard: endpoints, comparators, ground truth, sample size, analysis plan. Set the bar before the result arrives. * Build the measurement. Build, optimize and validate the LLM judges and rubrics that score the product at scale. Report their agreement with clinician ground truth, not their convenience, and retire the ones that drift. * Run it and write it up. Execute the evaluation, do the statistics, and write it up once in a form that serves the pod, the regulatory file and an academic submission. * Run post\-market surveillance. Monitor output quality in production and respond to regulatory feedback with data. Our clinical safety team triages complaints and incidents; you’re their counterpart in the pod, working out what their findings mean for the product and what should change. * Fix what the evidence finds. Prompt and rubric changes, evaluation harness changes, code changes in the pod’s codebase, shipped through the pod’s normal review and release process. * Publish. Contribute to peer\-reviewed literature on the translational benefit of the product. * Be the clinician in the room. Catch the output that reads well and is wrong. Hold the line on clinical nuance when a shortcut would ship faster. * Build for the next decade, not next quarter. Our targets are outrageous on purpose. The world's health doesn't have the luxury of incrementalism. * Lead, don't wait. We treat tomorrow's problems today. Sometimes we build what's needed before it's wanted, and we're fine with that. * Follow the evidence. Trust the patient. We pursue truth relentlessly. But when the subjective and objective disagree, we treat the patient, not the numbers. Ego is a comorbidity we can't afford. * Own the outcome. Everyone here carries the company. Raise problems with solutions, solve them end\-to\-end, and never be a bystander. * Ship, measure, go again. A button today, a workflow tomorrow. More iterations beat better planning. We're precise at pace, not reckless. * Live in clinicians' reality. Not the ideal workflow, the twenty\-patients\-before\-lunch actual one. We build for exhausted humans, and we'd better be decent ones while we do it. * Equity from day one. When Heidi wins, you win. You'll share directly in the success you help create. * Your health, covered. Comprehensive private medical and dental cover through Bupa, plus 24/7 mental health, coaching and wellbeing support through Sonder and a £100/month Healthy Heidi’s stipend. * Global parental leave. 26 weeks paid for primary carers and 18 weeks for secondary carers, subject to eligibility. * Fertility support. £7,000 one\-off payment, eligibility applies. * Learning \& development. £700 per year for courses, books, memberships, conferences and more. * Home office budget of £500 one\-off to set up a workspace you actually want to work in. * Recharge days after major milestones and busy periods so you can reset and come back strong. * Work from anywhere for up to 4 weeks per year, wherever the world takes you. * Clinical leave. 10 days per year for eligible clinical roles to maintain accreditation and requirements. * Flexibility that works. A hybrid environment, with 3 days in the office. Work Location: Sydney, Australia Availability: Full time
Job Title: Applied AI Specialist, Australia Company: Cloudera Job Category: Machine Learning Roles & Responsibilities: At Cloudera, we empower people to transform complex data into clear and actionable insights. With as much data under management as the hyperscalers, we're the preferred data partner for the top companies in almost every industry. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world’s largest enterprises. The Applied AI team exists to help the world's largest enterprises move beyond AI experimentation and into production. Our mission is to identify, validate, and accelerate high\-impact AI use cases that deliver measurable business outcomes across regulated and data\-intensive industries. Working at the intersection of industry expertise, AI technology, and enterprise data platforms, we partner directly with customers to solve complex business challenges using machine learning, computer vision, predictive analytics, generative AI, and agentic systems, while developing the technical conviction needed to move initiatives from concept to production. About the Role As an Applied AI Specialist, your mission is to identify, validate, and establish technical conviction around high\-impact private AI use cases that can be successfully deployed into production. Operating within a specialized regional pod, you will lead technical discovery, execute deep\-dive AI workshops, and collaborate closely with strategic ecosystem partners such as NVIDIA. You will work directly with enterprise architects, data scientists, platform teams, and business stakeholders to evaluate AI opportunities, assess technical feasibility, and define clear implementation paths. Your focus is on separating low\-conviction ideas from production\-ready opportunities, ensuring that only the highest\-value use cases advance into our engineering pipeline. Lead AI Discovery Workshops \- Partner with strategic ecosystem providers, including NVIDIA, to design and facilitate highly technical hands\-on workshops that identify, validate, and prioritize private AI opportunities. Develop Regional Domain Leadership \- Serve as a subject matter expert within your regional pod, building deep expertise in one or more strategic industries while helping transfer successful AI patterns across customer segments. Build Technical Assets \- Develop lightweight proofs of concept, reference architectures, technical demonstrations, and solution frameworks that help customers validate feasibility before committing to full\-scale implementation. Capture and Scale Best Practices \- Document successful use cases, architectural patterns, and implementation frameworks that can be reused across customers, industries, and regions. The Builder Mindset \- Strong technical foundation in data science. Comfortable working directly with code, APIs, notebooks, development frameworks, and enterprise architectures. Executive Communication Skills \- Exceptional ability to engage technical and executive audiences, facilitating conversations that connect business outcomes with practical implementation strategies. Centralized Platform Support \- You will never lose time troubleshooting cloud credentials, environment setup, or workshop preparation. A dedicated Global Workshop Platform Engineer builds, seeds, manages, and tears down workshop environments programmatically, allowing you to focus entirely on customer engagement and solution discovery. Direct Access to Industry Innovation \- You will work alongside leading AI practitioners, strategic ecosystem partners, and enterprise innovators to help shape how AI is deployed across some of the world's largest organizations. * Generous PTO Policy * Support work life balance with Unplugged Days * Flexible WFH Policy * Mental \& Physical Wellness programs * Phone and Internet Reimbursement program * Access to Continued Career Development * Comprehensive Benefits and Competitive Packages * Paid Volunteer Time * Employee Resource Groups Work Location: Sydney, NSW, Australia Availability: Full time
Job Title: Advanced Analytics Analyst Company: Commonwealth Bank of Australia Job Category: Machine Learning Roles & Responsibilities: * Build statistical and machine learning models that help solve real commercial lending and customer problems. * Join a highly experienced modelling team where you can develop specialist credit risk capability without needing previous credit risk experience. * Work on high\-impact initiatives spanning lending automation, merchant data, property analytics and model monitoring. We work on complex problems where the answer isn't always obvious. Rather than simply maintaining established models, we explore different data, methodologies and modelling approaches to understand a business problem and determine the right analytical solution. Our work spans areas including lending origination, servicing assessments, early warning and arrears, property analytics and the use of merchant data. We're a small, experienced team working on strategically important initiatives, and we're looking for an Advanced Analytics Analyst who is curious about data, enjoys solving problems and wants to develop their modelling capability in a supportive environment. In this role, you'll support the development and management of statistical and machine learning models that help us understand risk and make better decisions for our customers and business. * Support the development of statistical and machine learning models across commercial lending and credit\-related use cases. * Work with data to investigate business problems, identify patterns and determine appropriate analytical approaches. * Contribute to machine learning\-based origination scorecards and statistical modelling, including logistic regression. * Explore new data sources and methodologies, including merchant data, property analytics and forecasting. * Support model monitoring, implementation and ongoing model management. * Help translate analytical findings into meaningful customer and business outcomes. Work alongside experienced credit modelling specialists who can help you build your technical and domain expertise. * The team supports model implementation and works closely with the areas responsible for deployment, but does not own model deployment itself. If you're already part of the Commonwealth Bank Group (including Bankwest, x15ventures), you'll need to apply through Sidekick to submit a valid application. We’re keen to support you with the next step in your career. We're aware of some accessibility issues on this site, particularly for screen reader users. We want to make finding your dream job as easy as possible, so if you require additional support please contact HR Direct on 1800 989 696\. Work Location: Sydney, NSW, Australia Availability: Full time
Job Title: AI/ML Engineer Company: Vivanti Consulting Job Category: Machine Learning Roles & Responsibilities: We're the home base for talented technologists who want more and are looking to take their career to the next level by having more learning, more variety, more support and more chances to do meaningful work. The Role * Designing, training, and fine\-tuning machine learning models and LLMs to solve high\-value business problems * • Building robust MLOps pipelines to transition models smoothly from experimental notebooks to production * Setting up and maintaining the production components needed to distribute business intelligence downstream: model registries, job orchestration, experimentation, run telemetry, and the like * Developing Retrieval\-Augmented Generation (RAG) architectures and agentic workflows for enterprise applications * Ensuring AI solutions are scalable, secure, explainable, and cost\-effective * Collaborating closely with Data Engineers, Platform Engineers, and client stakeholders to embed intelligence into existing ecosystems * Models in production, not just in notebooks — you've shipped something real, and you've dealt with what happens after it goes live. * Strong Python and the ML stack — PyTorch or TensorFlow, Scikit\-learn, and the tooling around them. You should maintain a curiosity for unseen tooling and an appreciation for the fundamental concepts in ML. * Solid SQL experience is a must — including exposure to the entire database management lifecycle. Experience with medallion architecture and the implementation of data products is strongly favoured. * Real MLOps discipline — MLflow, Docker (Kubernetes is a bonus), CI/CD, and Terraform. You know what it takes to make models traceable, repeatable, and accessible to controlled development. * Databricks or Snowflake experience — MLflow, Feature Store, Cortex AI. Certification is ideal, but if you're not certified, we'll pay for it; we'll expect demonstrable hands\-on experience either way. * Cloud fluency — working knowledge of at least one of Azure ML, AWS SageMaker or GCP Vertex AI. * RAG know\-how — you've either implemented RAG to service a business need, or you can explain the implementation process end to end: from chunking strategies through to query processing and node searching. * Cost and performance instincts — you can illustrate and connect business value to the total cost of ownership for ML workloads, and you can distinguish the line between modelling utility and novelty. * Evaluation rigour — you can prove a model is doing what you claim, and know how best to demonstrate that to business\-level stakeholders (backtesting, known unknowns, multicollinearity risks, etc.). * Client\-ready communication — you can explain a technical trade\-off to a non\-technical stakeholder in language they understand. Your work matters and so do you. That's why we back your skills with a structure that supports your development, celebrates your wins, and helps you keep growing — professionally and personally. * A platform for growth: Work across industries, clients and technologies that stretch your thinking and build your personal and professional skills. * Mentoring Program: With a Senior Support Lead. * 360° Progress Reviews: Annual reviews based on honest feedback and clear goals. * Guilds \& Regular Training: Weekly training and learning from your peers and our key vendor partners. * Paid Certifications: Across all major technologies. * Hackathons \& Innovation Days: Challenge yourself, build cool stuff. * Kudos \& Recognition Programs: We celebrate wins, reward impact and offer long\-term incentives. * Socials \& Team Days: Monthly "fun for the sake of it" days, Friday socials, office drinks and snacks, video games, board games, and an F1 racing simulator. Work Location: Brisbane, Queensland, Australia Availability: Full time
Job Title: Staff Software Engineer Company: Commonwealth Bank Job Category: Machine Learning Roles & Responsibilities: * Help establish reusable AI\-powered document intelligence capabilities, accelerate intelligent automation and make it easier for teams to safely introduce new document types and use cases * Move AI beyond experimentation into trusted, scalable production services that materially improve how documents are processed across the organization Strengthen engineering capability and influence the broader technical direction of Document Management * You’ll operate as a trusted technical leader, working alongside senior technology leaders, architects and engineering peers to solve complex problems, influence technical direction and establish engineering patterns that can be reused at scale. The Document Management Crew is transforming how documents are captured, understood, processed and managed across the organisation. You will provide deep technical leadership as we build the next generation of intelligent document services. * Partner with senior technology leaders, architects, Staff and Principal Engineers and other engineering leaders to shape technical strategy, architecture and engineering standards across Document Management and adjacent technology domains * Lead the technical design of AI\-powered Intelligent Document Processing capabilities * Engineer solutions for document classification, information extraction, validation and transformation * Apply Generative AI, LLMs, machine learning and document intelligence to complex document\-processing problems * Establish reusable engineering patterns for prompt engineering, structured extraction, evaluation, confidence scoring and human\-in\-the\-loop processing * Take AI solutions from experimentation through to resilient, production\-ready services, while establishing appropriate AI guardrails, monitoring and engineering controls * Act as a trusted technical peer, bringing deep AI and engineering expertise to complex cross\-domain decisions and helping establish reusable patterns that can scale across the organisation Mentor and support engineers, helping uplift AI and software engineering capability across the crew. * At CommBank, we're committed to creating an accessible, inclusive and respectful workplace. If you require support or adjustments, please let us know. We welcome applications from people of all backgrounds and we're particularly committed to making a positive difference for Aboriginal and/or Torres Strait Islander Peoples. For support please contact 1800 989 696\. If you're already part of the Commonwealth Bank Group (including Bankwest, x15ventures), you'll need to apply through Sidekick to submit a valid application. We’re keen to support you with the next step in your career. We're aware of some accessibility issues on this site, particularly for screen reader users. We want to make finding your dream job as easy as possible, so if you require additional support please contact HR Direct on 1800 989 696\. Work Location: Australia Availability: Full time
