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Data Scientist Specialist

2 weeks ago

Brisbane, Queensland, Australia beBeeArtificial Full time $100,000 - $140,000
Senior AI Application Engineer

We are seeking a highly skilled Senior AI Application Engineer to join our team. The ideal candidate will have a strong background in data science and engineering, with experience in deploying machine learning pipelines, productionizing models, and streamlining orchestration processes.

This is a hands-on technical role that requires collaboration with Data Scientists and occasional work with the Software Engineering and Delivery Team. The successful candidate will be passionate about operationalizing AI/ML and comfortable working in a modern data platform like Databricks.

Key Responsibilities
  • Collaborate with Data Scientists to build and maintain ML and data pipelines using Databricks (PySpark, Delta Lake, MLflow).
  • Design and implement orchestration workflows using tools like Databricks Workflows.
  • Manage model deployment, versioning, and lifecycle using MLflow or similar tools.
  • Set up and monitor CI/CD pipelines for data science and ML applications.
  • Build simple backend services (e.g., REST APIs) or lightweight frontends to support demo applications or PoCs.
  • Ensure code quality, modularity, and reusability across pipelines and tools.
  • Contribute to documentation, tooling, and infrastructure to accelerate experimentation and delivery.
  • Work with DevOps/Infra teams to ensure scalable, secure, and efficient operation of ML services.
Requirements
  • Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or a related field.
  • Solid Python and SQL programming skills, especially in data and ML contexts.
  • 2-5 years' experience with Databricks or equivalent data platforms.
  • Familiarity with ML lifecycle tools (MLflow, etc.).
  • Understanding of modern orchestration tools.
  • Experience with Git and CI/CD tools (e.g., GitHub Actions, Azure DevOps).
  • Knowledge of REST API development (e.g., FastAPI, Flask) and basic frontend skills (optional but a plus).
  • Familiarity with cloud platforms (AWS, Azure, or GCP).