AI Data Engineer
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Contract AI Data Engineer for a Federal Government Department, building scalable data pipelines and AI infrastructure for a National Skills Taxonomy. Day to day: operationalising ML, NLP and generative AI with Python, cloud platforms, model-serving APIs and MLOps/DevOps practices, working alongside data scientists.
Salary: $120 – $160 per hour
A Federal Government Department is looking to engage an AI Data Engineer to support the delivery of a range of AI and data engineering solutions. This role will be working closely with the Data Scientists to operationalise machine learning, NLP and generative AI.
Contract Details:
Initial contract to June 30 2027 with a 12 month extension options out to June 30 2028
Estimated start date October 2026 (pending onboarding and availability)
A Baseline Security clearance required (you must be an Australian Citizen to go through the vetting process).
Full time 40 hour work week. Hourly rate contract
Preferred Location: Canberra, ACT. This role can also be located in NSW, VIC or QLD
Hybrid working options
Key Duties and Responsibilities:
The specialist will design, develop and maintain scalable data and AI infrastructure that supports the collection, preparation, validation and operationalisation of skills data and analytical models. They will work closely with Data Scientists, Information Management Specialists and other technical and policy specialists to develop robust, repeatable and production-ready capabilities that support the ongoing development and use of a National Skills Taxonomy.
The specialist will contribute to the design, implementation and continuous improvement of data pipelines, validation frameworks, model-serving capabilities and technical infrastructure that support the NST. They will work alongside Data Scientists, Information Management Specialists and domain experts to ensure technical solutions are scalable, reliable, transparent and aligned with NST governance, quality and operational requirements.
Required Skills:
Designing, developing and maintaining scalable data ingestion, transformation and processing pipelines for structured and unstructured data sources.
Advanced proficiency in Python and modern data engineering, including managing large-scale datasets, automating workflows, scalable pipelines, APIs, cloud platforms and distributed processing.
Proven ability to operationalise machine learning, NLP and generative AI using robust data quality, metadata, lineage, reproducibility, DevOps and MLOps practices.
Applying modern data engineering practices to support the collection, preparation, cleansing, validation and integration of skills-related datasets.
Designing and implementing repeatable validation pipelines that support the assessment, monitoring and quality assurance of AI and NLP model outputs.
Collaborating with Data Scientists to operationalise machine learning, NLP and Generative AI solutions within scalable production environments.
Developing and maintaining model-serving, deployment and API integration capabilities that support analytical products and downstream systems.
Implementing data governance, metadata management, lineage tracking and versioning practices to support transparency, traceability and reproducibility.
Developing and maintaining cloud-based and distributed data processing environments capable of supporting large-scale data and AI workloads.
Applying software engineering, DevOps and MLOps practices including source control, automated testing, continuous integration and technical documentation.
Supporting the ongoing enhancement, maintenance and operationalisation of the NST's technical infrastructure, data assets and AI-enabled capabilities.
Demonstrated experience designing and maintaining scalable data pipelines, automation processes, bulk processing workflows and cloud or distributed data environments that support analytical and AI-enabled products.
Demonstrated experience deploying machine learning, NLP or Generative AI solutions into production, including APIs, model serving, testing, validation, monitoring, version control and MLOps or DevOps practices.
What is on offer
The chance to work on a project that will deliver advanced analytics outcomes with the latest technologies
The opportunity to work on a long term/stable project with clearly defined outcomes
An initial contract to June 30 2027 with a 12 month extension option out to June 30 2028
How to apply
If you would like to apply for this role please click the quick apply button or email Liam O'Meara at ••••@datadiv.com.au
