Experis
Machine Learning Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer on a 6–12 month contract in London (Hybrid). Requires strong Python skills, experience in deploying ML models, and proficiency with cloud services (AWS, GCP, Azure). Competitive day rate offered.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
-
💰 - Day rate
Unknown
-
🗓️ - Date
October 3, 2025
🕒 - Duration
More than 6 months
-
🏝️ - Location
Hybrid
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
London Area, United Kingdom
-
🧠 - Skills detailed
#ML (Machine Learning) #Monitoring #Forecasting #Azure #Airflow #Kubernetes #PyTorch #TensorFlow #NLP (Natural Language Processing) #MLflow #Scala #Docker #GCP (Google Cloud Platform) #Programming #Data Pipeline #Distributed Computing #Python #Cloud #AWS (Amazon Web Services) #AI (Artificial Intelligence) #Deployment #Spark (Apache Spark) #Data Science
Role description
We are seeking a highly skilled Machine Learning Engineer to join our team on a contract basis. You will be responsible for designing, building, and deploying machine learning models into production, working closely with data scientists, software engineers, and product teams to deliver scalable AI solutions. This is an excellent opportunity for someone who thrives in fast-paced environments and enjoys solving complex problems with real-world impact.
Key Responsibilities
• Develop, train, and optimize machine learning models for production use.
• Collaborate with data scientists to turn research prototypes into production-grade solutions.
• Build robust data pipelines and feature engineering workflows.
• Deploy ML solutions into cloud environments (AWS, GCP, or Azure).
• Implement monitoring, testing, and model performance evaluation frameworks.
• Work with engineering teams to ensure seamless integration of ML models into products.
• Contribute to improving infrastructure, tooling, and best practices for ML development and deployment.
Skills & Experience
Essential:
• Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn).
• Proven experience in developing and deploying machine learning models in production.
• Solid understanding of data structures, algorithms, and software engineering principles.
• Experience with ML pipelines and orchestration tools (e.g., Airflow, Kubeflow, MLflow).
• Proficiency in working with cloud services (AWS, GCP, or Azure).
• Strong understanding of CI/CD, containerisation (Docker), and orchestration (Kubernetes).
• Excellent problem-solving skills and ability to work independently in a fast-paced environment.
Desirable:
• Experience with NLP, computer vision, or time-series forecasting.
• Familiarity with distributed computing frameworks (Spark, Ray).
• Experience with MLOps and model governance practices.
• Previous contract experience in a similar ML engineering role.
Contract Details
• Duration: 6–12 months (extension possible)
• Location: London (Hybrid working model)
• Day Rate: Competitive, depending on experience
We are seeking a highly skilled Machine Learning Engineer to join our team on a contract basis. You will be responsible for designing, building, and deploying machine learning models into production, working closely with data scientists, software engineers, and product teams to deliver scalable AI solutions. This is an excellent opportunity for someone who thrives in fast-paced environments and enjoys solving complex problems with real-world impact.
Key Responsibilities
• Develop, train, and optimize machine learning models for production use.
• Collaborate with data scientists to turn research prototypes into production-grade solutions.
• Build robust data pipelines and feature engineering workflows.
• Deploy ML solutions into cloud environments (AWS, GCP, or Azure).
• Implement monitoring, testing, and model performance evaluation frameworks.
• Work with engineering teams to ensure seamless integration of ML models into products.
• Contribute to improving infrastructure, tooling, and best practices for ML development and deployment.
Skills & Experience
Essential:
• Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn).
• Proven experience in developing and deploying machine learning models in production.
• Solid understanding of data structures, algorithms, and software engineering principles.
• Experience with ML pipelines and orchestration tools (e.g., Airflow, Kubeflow, MLflow).
• Proficiency in working with cloud services (AWS, GCP, or Azure).
• Strong understanding of CI/CD, containerisation (Docker), and orchestration (Kubernetes).
• Excellent problem-solving skills and ability to work independently in a fast-paced environment.
Desirable:
• Experience with NLP, computer vision, or time-series forecasting.
• Familiarity with distributed computing frameworks (Spark, Ray).
• Experience with MLOps and model governance practices.
• Previous contract experience in a similar ML engineering role.
Contract Details
• Duration: 6–12 months (extension possible)
• Location: London (Hybrid working model)
• Day Rate: Competitive, depending on experience
