Machine Learning Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer on a 6-month rolling contract, remote, with a pay rate outside IR35. Key skills include Python, SQL, AWS, MLOps frameworks, and data engineering tools. Experience in ETL processes and agile environments is required.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
-
💰 - Day rate
-
🗓️ - Date discovered
September 13, 2025
🕒 - Project duration
More than 6 months
-
🏝️ - Location type
Remote
-
📄 - Contract type
Outside IR35
-
🔒 - Security clearance
Unknown
-
📍 - Location detailed
United Kingdom
-
🧠 - Skills detailed
#Monitoring #Data Quality #SageMaker #SQL (Structured Query Language) #Data Modeling #Scala #Data Engineering #Deployment #dbt (data build tool) #Data Integrity #Spark (Apache Spark) #Python #Programming #MLflow #Model Deployment #Agile #AWS (Amazon Web Services) #Airflow #Security #Docker #Kafka (Apache Kafka) #"ETL (Extract #Transform #Load)" #Kubernetes #ML (Machine Learning) #AI (Artificial Intelligence) #Data Pipeline #Data Science
Role description
MLOps Data Engineer - Contract - Outside IR35
• Remote based
• 6 months rolling (long term contract)
• Outside IR35 contract
MLOps Data Engineer role overview:
You will be designing, building and maintaining data pipelines and machine learning infrastructure that support scalable, reliable, and production-ready AI/ML solutions. You will work closely with data scientists, engineers, and product teams to operationalize models, streamline workflows, and ensure data quality and availability.
• Develop and maintain data pipelines to support machine learning and analytics use cases.
• Implement MLOps best practices for model deployment, monitoring, and lifecycle management.
• Build and optimize ETL/ELT processes for structured and unstructured data.
• Automate workflows for training, testing, and deploying ML models.
• Ensure data integrity, governance, and security across the ML lifecycle.
MLOps Data Engineer Experience
• Strong programming skills in Python, SQL, and experience with AWS
• Proficiency with data engineering tools (e.g., Spark, Kafka, Airflow, dbt).
• Hands-on experience with MLOps frameworks (e.g., MLflow, Kubeflow, Vertex AI, SageMaker).
• Familiarity with CI/CD pipelines, containerization (Docker, Kubernetes)
• Solid understanding of data modeling, warehousing, and APIs.
• Strong problem-solving skills and ability to work in agile environments.
MLOps Data Engineer - Contract - Outside IR35
• Remote based
• 6 months rolling (long term contract)
• Outside IR35 contract
MLOps Data Engineer role overview:
You will be designing, building and maintaining data pipelines and machine learning infrastructure that support scalable, reliable, and production-ready AI/ML solutions. You will work closely with data scientists, engineers, and product teams to operationalize models, streamline workflows, and ensure data quality and availability.
• Develop and maintain data pipelines to support machine learning and analytics use cases.
• Implement MLOps best practices for model deployment, monitoring, and lifecycle management.
• Build and optimize ETL/ELT processes for structured and unstructured data.
• Automate workflows for training, testing, and deploying ML models.
• Ensure data integrity, governance, and security across the ML lifecycle.
MLOps Data Engineer Experience
• Strong programming skills in Python, SQL, and experience with AWS
• Proficiency with data engineering tools (e.g., Spark, Kafka, Airflow, dbt).
• Hands-on experience with MLOps frameworks (e.g., MLflow, Kubeflow, Vertex AI, SageMaker).
• Familiarity with CI/CD pipelines, containerization (Docker, Kubernetes)
• Solid understanding of data modeling, warehousing, and APIs.
• Strong problem-solving skills and ability to work in agile environments.
