Machine Learning Engineer - AWS Migration
Posted 2 weeks ago by TechNET IT Recruitment Limited
Negotiable
Outside
Hybrid
London, UK
Summary: We are looking for a Machine Learning Engineer to facilitate the migration of model training and deployment pipelines from an on-prem Kubernetes platform to AWS. This hands-on role requires expertise in ML engineering, Python development, and AWS, particularly in building production-grade ML pipelines using SageMaker. The consultant will adapt existing workflows to AWS-native services while ensuring performance and scalability. The position is contract-based, outside IR35, and hybrid in London.
Key Responsibilities:
- Migrate ML workflows (training, deployment, monitoring) from on-prem Kubernetes to AWS SageMaker.
- Rewrite/refactor code to align with AWS-native services and best practices.
- Build & optimise Python-based ML pipelines for scalable, production-ready deployment.
- Collaborate with Data Science & DevOps teams to ensure a smooth transition.
- Implement robust model monitoring, versioning, and CI/CD for ML.
Key Skills:
- Strong experience as a Machine Learning Engineer or ML-focused Software Engineer.
- Proven track record building ML pipelines in AWS SageMaker.
- Python development for ML automation & deployment.
- Containerised ML workflows (Docker, Kubernetes).
- Experience migrating ML systems from on-prem to cloud.
Salary (Rate): undetermined
City: London
Country: UK
Working Arrangements: hybrid
IR35 Status: outside IR35
Seniority Level: undetermined
Industry: IT
Machine Learning Engineer - AWS Migration
Contract | Outside IR35 | London Hybrid | 6 months+
We are seeking an experienced Machine Learning Engineer to assist in our client's migration of their model training and deployment pipelines from an on-prem Kubernetes-based platform to AWS. This role is hands-on and will involve adapting existing workflows and tooling to AWS-native services, ensuring minimal disruption while optimising for performance and scalability.
The ideal consultant will have a strong mix of ML engineering, Python development, and AWS expertise, with proven experience building production-grade ML pipelines in SageMaker.
What you'll be doing:
- Migrate ML workflows (training, deployment, monitoring) from on-prem Kubernetes to AWS SageMaker.
- Rewrite/refactor code to align with AWS-native services and best practices.
- Build & optimise Python-based ML pipelines for scalable, production-ready deployment.
- Collaborate with Data Science & DevOps teams to ensure a smooth transition.
- Implement robust model monitoring, versioning, and CI/CD for ML.
What we're looking for:
- Strong experience as a Machine Learning Engineer or ML-focused Software Engineer.
- Proven track record building ML pipelines in AWS SageMaker.
- Python development for ML automation & deployment.
- Containerised ML workflows (Docker, Kubernetes).
- Experience migrating ML systems from on-prem to cloud.
Nice to have:
- GPU-enabled Kubernetes cluster experience.
- MLOps best-practice knowledge.
- Familiarity with AWS services like Lambda, Step Functions, S3, ECR.