

RED Global
Machine Learning Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer (MLOps Engineer) in London, UK, for 6 months at a competitive rate. Requires 5+ years of experience, expertise in GCP Vertex AI, Python, CI/CD, and strong MLOps practices. Financial services experience is a plus.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
Unknown
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🗓️ - Date
July 2, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
Fixed Term
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🔒 - Security
Unknown
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📍 - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#Infrastructure as Code (IaC) #FastAPI #Deployment #Agile #GCP (Google Cloud Platform) #Flask #Monitoring #Python #Scala #Leadership #GIT #AI (Artificial Intelligence) #Terraform #ML (Machine Learning) #Automation #Azure #Cloud #Unit Testing #Docker #Data Science #AWS (Amazon Web Services) #Data Engineering
Role description
We're Hiring:
Role: MLOps Engineer
Duration: 6 Months (Plus possible extension)
Location: London, UK (Hybrid)
Experience: 5+ Years
We are looking for an experienced MLOps Engineer to join a growing ML Engineering team and drive the deployment, monitoring, and optimization of machine learning solutions in production. The ideal candidate will have strong expertise in GCP Vertex AI, Python development, cloud infrastructure, and MLOps best practices.
Key Skills & Experience
• 5+ years of experience in Machine Learning Engineering/MLOps.
• Strong hands-on experience with GCP Vertex AI (essential); Azure experience is a plus.
• Expertise in Python, Flask/FastAPI, OOP, unit testing, and software engineering best practices.
• Experience with CI/CD pipelines, Docker, Terraform/IaC, Git, and cloud platforms (GCP/AWS/Azure).
• Proven experience deploying, monitoring, and maintaining ML models in production environments.
• Strong understanding of ML lifecycle management, model monitoring, model registries, and automation.
• Experience working in Agile environments and collaborating with Data Scientists, Data Engineers, and Platform Teams.
• Leadership or mentoring experience is highly desirable.
Key Responsibilities
• Build and maintain scalable ML infrastructure and deployment pipelines.
• Develop APIs for model serving and integration with enterprise applications.
• Design and implement automated ML workflows covering training, deployment, monitoring, and retraining.
• Ensure reliability, performance, and scalability of cloud-based ML services.
• Drive MLOps best practices and support the transition from PoC to production-grade ML platforms.
• Mentor engineers and contribute to technical leadership within the team.
Nice to Have
• Experience in Financial Services or Insurance domains.
• Exposure to regulated environments.
• Azure ML and advanced cloud architecture experience.
📩 If you're interested, please share your updated CV on aknair@redglobal.com
We're Hiring:
Role: MLOps Engineer
Duration: 6 Months (Plus possible extension)
Location: London, UK (Hybrid)
Experience: 5+ Years
We are looking for an experienced MLOps Engineer to join a growing ML Engineering team and drive the deployment, monitoring, and optimization of machine learning solutions in production. The ideal candidate will have strong expertise in GCP Vertex AI, Python development, cloud infrastructure, and MLOps best practices.
Key Skills & Experience
• 5+ years of experience in Machine Learning Engineering/MLOps.
• Strong hands-on experience with GCP Vertex AI (essential); Azure experience is a plus.
• Expertise in Python, Flask/FastAPI, OOP, unit testing, and software engineering best practices.
• Experience with CI/CD pipelines, Docker, Terraform/IaC, Git, and cloud platforms (GCP/AWS/Azure).
• Proven experience deploying, monitoring, and maintaining ML models in production environments.
• Strong understanding of ML lifecycle management, model monitoring, model registries, and automation.
• Experience working in Agile environments and collaborating with Data Scientists, Data Engineers, and Platform Teams.
• Leadership or mentoring experience is highly desirable.
Key Responsibilities
• Build and maintain scalable ML infrastructure and deployment pipelines.
• Develop APIs for model serving and integration with enterprise applications.
• Design and implement automated ML workflows covering training, deployment, monitoring, and retraining.
• Ensure reliability, performance, and scalability of cloud-based ML services.
• Drive MLOps best practices and support the transition from PoC to production-grade ML platforms.
• Mentor engineers and contribute to technical leadership within the team.
Nice to Have
• Experience in Financial Services or Insurance domains.
• Exposure to regulated environments.
• Azure ML and advanced cloud architecture experience.
📩 If you're interested, please share your updated CV on aknair@redglobal.com






