M/LOps Engineer

NTT DATA, Inc.; Perth; Hybrid; AUD 120,000 - 180,000; Full time

Benefits offered by this job

Hybrid work environment

Perth CBD location

Job summary

NTT Data are seeking an experienced M/LOps Engineer to join a major data and analytics program delivering forecasting and predictive modelling capabilities. The role is based in Perth CBD with a hybrid work environment, four days onsite, starting ASAP until 30 June 2027.

You will build production-grade ML pipelines on Databricks, implement MLflow, CI/CD and governance, and collaborate with data scientists, engineers and architects to productionise analytical workloads in a scalable cloud-scale

Qualifications

• Strong software engineering background with ML/AI pipelines.
• Experience with Databricks ecosystem and MLflow.
• Hands-on Apache Spark and distributed data processing.
• Advanced R development with Sparklyr or SparkR.
• Experience shipping production ML or analytics solutions.
• Understanding of large-scale data processing and data governance.

Responsibilities

• Build, test and optimise production-grade ML and data pipelines using Databricks and Spark.
• Design and implement MLOps frameworks for deployment, versioning, monitoring and retraining.
• Develop scalable solutions with CI/CD and automated testing.
• Optimise R-based forecasting workloads with Sparklyr and SparkR.
• Collaborate with data architects and stakeholders to integrate models into systems.
• Monitor platform performance, reliability and data integrity in production.
• Manage Databricks workloads, MLflow, and model lifecycle processes.
• Support governance, lineage and best practices across ML solutions.

Skills

Databricks

MLflow

Spark

R programming

CI/CD

Git

Distributed data

Tools

Sparklyr

SparkR

Unity Catalog

Delta Lake

Job description

NTT Data are seeking an experienced M/LOps Engineer to join a major data and analytics program delivering advanced forecasting and predictive modelling capabilities.

• Contract through to end of June 2027
• Perth CBD location, ASAP start
• Hybrid work environment – 4 days per week onsite

This is an exciting opportunity to work at the intersection of machine learning, software engineering and cloud-scale data platforms, helping to productionise, automate and optimise analytical solutions within a modern Databricks environment.

Working closely with data scientists, data engineers and architects, you'll play a key role in building scalable machine learning pipelines, automating model lifecycles and ensuring analytical workloads are reliable, secure and production-ready.

Key Responsibilities

• Build, test and optimise production-grade machine learning and data processing pipelines using Databricks and Apache Spark
• Design and implement MLOps frameworks supporting model deployment, versioning, monitoring and automated retraining
• Develop scalable and maintainable solutions using software engineering best practices, including automated testing and CI/CD
• Optimise and productionise R-based forecasting and statistical modelling workloads using Sparklyr and SparkR
• Collaborate with data architects, engineers and business stakeholders to integrate predictive models into downstream systems
• Monitor platform performance, pipeline reliability and data integrity across production environments
• Manage Databricks workloads, MLflow implementations and model lifecycle processes
• Support data governance, lineage and operational best practices across machine learning solutions
• Contribute to architecture discussions and continuous improvement of engineering standards

Skills & Experience

• Strong software engineering background with experience in design patterns, testing, Git and CI/CD practices
• Proven experience working within the Databricks ecosystem including MLflow, Unity Catalog and workload orchestration
• Strong hands‑on experience with Apache Spark and distributed data processing
• Advanced R development skills, including experience with Sparklyr or SparkR
• Experience building and supporting production machine learning or advanced analytics solutions
• Strong understanding of large‑scale data processing, Delta Lake and complex data environments
• Experience working with time‑series, forecasting or statistical modelling workloads
• Excellent problem‑solving, communication and stakeholder engagement skills 

Nice to Have

• Python …
• Experience…