Machine Learning Engineer

Job Title: Machine Learning Engineer Company: TaskVerse Job Category: Machine Learning Roles & Responsibilities: About The Role Bailey Abbott is seeking a Machine Learning Engineer with a strong software engineering foundation to help productionise, scale, and maintain advanced analytical and predictive models. You will connect data science experimentation with dependable engineering, enabling models and analytical workloads to run effectively in production. Working within a Databricks environment, you will develop scalable data pipelines and automated machine learning lifecycles using Apache Spark, R, and modern engineering practices. You will collaborate with data scientists, data engineers, architects, and domain specialists to turn analytical solutions into maintainable services and workflows. This role suits someone who enjoys solving technical problems, improving reliability, and making complex systems easier to operate. You should be comfortable querying relational data and working with Delta Lake or comparable data formats, as well as large tabular or time\-series datasets. Familiarity with Python or PySpark, cloud platforms such as Azure, AWS, or GCP, Infrastructure as Code, model monitoring, data lineage, or enterprise governance would be beneficial. Responsibilities Design, build, test, and optimise production\-grade data processing and model training pipelines in Apache Spark and Databricks. Develop repeatable workflows that support reliable model deployment, versioning, monitoring, and retraining, using MLflow and CI/CD practices where appropriate. Partner with data architects, data engineers, analysts, and other stakeholders to integrate predictive outputs into downstream systems and analytical platforms. Monitor pipeline performance and reliability, help manage cluster sizing, and support data integrity, governance, and maintainability across production workspaces. Work Location: Australia Availability: Full time

Qualifications You will bring practical experience building and supporting production data or machine learning solutions, together with a sound understanding of software engineering principles. This includes designing modular code, using Git for version control, writing unit and integration tests, and working with CI/CD pipelines. Hands\-on experience with Databricks is important, including orchestrating workloads and working with tools such as MLflow and Unity Catalog. You will have a strong understanding of Apache Spark, including distributed processing, partitioning, query optimisation, and memory management. Proficiency in R for statistical modelling, data manipulation, or forecasting is required, along with experience using SparkR or sparklyr to work with distributed data. Benefits At Bailey Abbott, you will work with collaborative colleagues and contribute to varied client challenges across public and private sectors. The role offers opportunities to apply modern data and machine learning technologies to meaningful problems while strengthening your engineering practice. You will be encouraged to share ideas, explore better ways of working, and develop your skills through exposure to different teams, technologies, and business contexts. Our people\-focused culture values ownership, constructive collaboration, and continuous improvement. Key Skills: Machine Learning, Python, Model Training Salary: Not disclosed