Lead AI Engineer

A permanent job opportunity for an AI Engineer position based in Melbourne East. **Australia PR / Citizes are encouraged to apply**
Your new company
A complex, value-driven organisation operating within a highly regulated environment, this organisation is undergoing significant transformation to position itself for long-term growth, resilience, and innovation.
Your new role
The Lead AI Engineer plays a strategic and influential role in advancing the organisation's data and AI capability within the Enterprise Data & Analytics (EDA) function. The role drives business value and enterprise performance by designing, developing, and operationalising AI and machine learning solutions that inform decision-making, optimise operations, and enable predictive and prescriptive insights.
The role champions the adoption of Databricks, Azure, and modern AI frameworks to accelerate intelligent automation, enable actionable insights, and embed innovation across the organisation, positioning AI as a driver of enterprise strategy and long-term value creation.
In this role you will,

Design, develop, and deploy end-to-end AI and Machine Learning solutions that deliver measurable business value, improve operational efficiency and enhance customer outcomes.

Apply advanced machine learning, deep learning, and generative AI techniques including but not limited to NLP, transformer models, and LLM fine-tuning to generate actionable insights and intelligent automation that improve decision making and service reliability.

Accelerate innovation and experimentation through enterprise data platforms such as Databricks, MLflow, and Delta Lake, or equivalent technologies, to enable rapid prototyping and faster delivery of AI driven value.

Leverage cloud-based AI and ML platforms (e.g., Azure AI Services, Azure OpenAI, or other platforms) to develop and deploy models at scale ensuring performance, scalability and resilience.

Support the integration of AI models into enterprise applications and data workflows to enhance business intelligence, automation and customer experience.

Optimise models for performance, scalability, and accuracy in distributed environments delivering efficient and cost-effective AI systems capable of handling enterprise scale workloads.

Apply DevOps and Infrastructure-as-Code practices (e.g., Docker, Kubernetes, CI/CD) to automate deployment processes reducing manual effort and operational risk.

Ensure all AI solutions comply with data governance, ethics, and responsible AI principles ensuring AI practices meet ethical, privacy and security standards.

What you'll need to succeed

Minimum 6 - 8 years experience in Software and Data Engineering using Python and TypeScript

Demonstrated experience in Databricks Machine Learning, including MLflow, AutoML, Delta Lake, and Spark

Deep hands-on experience with Machine Learning and Deep Learning frameworks such as TensorFlow, PyTorch, and Scikit-learn

Proven capability in MLOps practices, including model tracking, deployment, monitoring, and CI/CD pipelines

Proficiency with cloud platforms, preferably Azure, and Databricks Lakehouse architecture including Unity Catalog

Experience working with Transformer-based and Generative AI models, including LLMs, LangChain, LlamaIndex, and Semantic Kernel

Advanced skills in Data Engineering and large-scale data processing using Delta Lake, Spark, and PySpark

Strong DevOps and Infrastructure-as-Code expertise with Docker, Kubernetes, AKS, Terraform, and CI/CD

What you'll get in return

A permanent job opportunity with flexible work arrangements.

Working in an esteemed organisation where they develop and grow careers.

Excellent salary and benefits. Do not miss out!

What you need to do now
If you're interested in this role or know of someone that may be, please click 'Apply Now' or forward an updated CV to [email protected] #2988138