AI/ML Engineer
Posted 3 days ago by Coltech
Negotiable
Inside
Hybrid
Sheffield, England, United Kingdom
Summary: The Senior AI/ML Engineer role focuses on leveraging cloud engineering skills to develop and deploy AI and machine learning solutions on Google Cloud Platform (GCP). Candidates should have extensive experience with Kubernetes and GKE, as well as a strong background in AI engineering and data science. This contract position requires collaboration with various teams to optimize ML models and ensure operational excellence. The role is hybrid with flexibility based on client needs and is classified as inside IR35.
Key Responsibilities:
- Design, build, and deploy AI/ML solutions in production environments
- Develop scalable ML pipelines and AI applications on GCP
- Deploy and manage containerised applications using Kubernetes and GKE
- Collaborate with data engineers, architects, and platform teams
- Optimise ML models and cloud infrastructure for performance and scalability
- Implement CI/CD pipelines and MLOps best practices
- Work with large datasets and modern data processing frameworks
- Ensure platform reliability, security, and operational excellence
Key Skills:
- 5+ years of experience in AI Engineering, Machine Learning, Data Science, and Cloud Engineering
- Strong hands-on experience with Google Cloud Platform (GCP), Google Kubernetes Engine (GKE), and Kubernetes
- Experience with Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
- Knowledge of MLOps and deployment automation
- Experience with containerisation tools such as Docker
- Familiarity with CI/CD pipelines and DevOps practices
- Strong problem-solving and stakeholder communication skills
Salary (Rate): undetermined
City: Sheffield
Country: United Kingdom
Working Arrangements: hybrid
IR35 Status: inside IR35
Seniority Level: undetermined
Industry: IT
Senior AI/ML Engineer – GCP, GKE & Kubernetes (Contract) Location Bristol / Sheffield / Leeds, United Kingdom Hybrid / On-site flexibility depending on client requirements Contract Inside IR35 Experience Required - 5+ Years
Role Overview We are seeking experienced AI/ML professionals with strong cloud engineering capabilities to join a growing delivery team working on modern AI and data-driven platforms. This contract role is ideal for engineers who have hands-on expertise across Machine Learning, AI Engineering, Data Science, and scalable cloud-native deployments on Google Cloud Platform (GCP). The ideal candidate will have deep experience with Kubernetes and Google Kubernetes Engine (GKE), along with a strong understanding of production-grade AI/ML systems.
Key Responsibilities
- Design, build, and deploy AI/ML solutions in production environments
- Develop scalable ML pipelines and AI applications on GCP
- Deploy and manage containerised applications using Kubernetes and GKE
- Collaborate with data engineers, architects, and platform teams
- Optimise ML models and cloud infrastructure for performance and scalability
- Implement CI/CD pipelines and MLOps best practices
- Work with large datasets and modern data processing frameworks
- Ensure platform reliability, security, and operational excellence
Required Skills & Experience
- 5+ years of experience in: AI Engineering Machine Learning Data Science Cloud Engineering
- Strong hands-on experience with: Google Cloud Platform (GCP) Google Kubernetes Engine (GKE) Kubernetes
- Experience with Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
- Knowledge of MLOps and deployment automation
- Experience with containerisation tools such as Docker
- Familiarity with CI/CD pipelines and DevOps practices
- Strong problem-solving and stakeholder communication skills
Preferred Skills
- Experience with Vertex AI
- Knowledge of Terraform or Infrastructure as Code
- Exposure to streaming/data platforms such as Kafka or Spark
- Experience in enterprise or consulting environments
Contract Details Contract opportunity Competitive day rates Immediate or short-notice starters preferred Roles available across Bristol, Sheffield, and Leeds