About the Role
I'm currently working with an exciting client who is looking for an experienced Machine Learning Engineer to join their team on a contract basis. You'll be designing and deploying ML models and pipelines at scale, working closely with data scientists, engineers, and stakeholders both on-site and remotely.
Key Responsibilities
- Design, build, and deploy machine learning models and pipelines into production
- Develop and maintain Python-based ML solutions and supporting tooling
- Leverage AWS cloud services to host, scale, and monitor ML workloads
- Collaborate with data science teams to operationalise models (MLOps)
- Contribute to CI/CD pipelines and best practices for ML deployments
- Participate in architecture discussions and technical reviews
Required Skills
- Strong hands‑on experience with Python for ML development
- Proficient with AWS ML and cloud services (SageMaker, S3, Lambda, EC2, IAM, etc.)
- Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit‑learn
- Familiarity with MLOps practices and tools (MLflow, Kubeflow, or similar)
- Experience with data processing and feature engineering at scale
- Strong communication and ability to work independently in a contract environment
Nice to Have
- Experience with LLMs, generative AI, or NLP pipelines
- Familiarity with containerisation (Docker, Kubernetes/EKS)
- Knowledge of monitoring and observability tools (CloudWatch, Datadog, Grafana)
- Inside IR35
- ASAP / To be confirmed
- Initial contract: 6 months rolling
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