Machine Learning Engineer

Queen Square

Wokingham, UK

6 days ago

Role details

Contract type

Temporary contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Compensation

£119,600.0

Working hours

Regular working hours

Job source

find.jobs

Tech stack

Microsoft Azure Big Data Cloud Storage Continuous Integration Information Engineering DevOps JSON Python (Programming Language) Machine Learning SQL Azure NetCDF NoSQL

+17 more

Tensorflow Azure DevOps Pipelines Azure Machine Learning SQL Databases Management of Software Versions Parquet Data Logging Azure Data Factory Pytorch Autoscaling System Availability Delivery Pipeline Scikit Learn Data Lineage Machine Learning Operations Data Pipelines Docker

Job description

Our client is seeking an experienced Azure MLOps Engineer to support the deployment, automation, and management of machine learning solutions within Azure. Working closely with architects, data scientists, forecasting teams, developers, and DevOps engineers, you will help deliver scalable, secure, and reliable MLOps platforms supporting large-scale data processing and real-time inference workloads., * Deploy and manage ML models in production using Azure Machine Learning.

Design and maintain Azure-based MLOps infrastructure.
Build and support Azure DevOps CI/CD pipelines for ML artefacts.
Implement monitoring, logging, security, and governance controls.
Manage data pipelines, storage solutions, data versioning, and lineage tracking.
Support real-time inference and scalable ML workloads, including auto-scaling.
Collaborate with technical and business stakeholders to optimise model performance and platform reliability.
Produce and maintain technical documentation.

Requirements

5+ years’ experience in MLOps, DevOps, or related engineering roles.
Strong knowledge of the ML lifecycle and production ML operations.
Hands-on experience with Azure Machine Learning and MLOps frameworks.
Experience with Azure DevOps, CI/CD pipelines, and automation.
Strong Python skills and experience with TensorFlow, PyTorch, or Scikit-learn.
Experience with Docker, Azure SQL Database, Storage Accounts, Blob Storage, and SQL/NoSQL technologies.
Experience monitoring and supporting production ML environments.
Knowledge of data engineering practices and tools.
Familiarity with GRIB, NetCDF, Parquet, and JSON is advantageous.
Azure Data Scientist Associate certification is desirable.