Duration: Initial 6 months (with strong extension potential)
About the RoleWe’re working with a leading organisation seeking a skilled Machine Learning Engineer to support the development and deployment of scalable ML solutions.This is a hands-on contract role, ideal for someone who can take models from concept to production, working closely with data scientists, engineers, and stakeholders to deliver high-impact machine learning capabilities.
Key Responsibilities
1. Design, build, and deploy production-grade machine learning models
2. Develop and maintain data pipelines and feature engineering workflows
3. Collaborate with data scientists to operationalise models and improve performance
4. Implement MLOps best practices, including CI/CD, monitoring, and versioning
5. Optimise models for scalability, reliability, and performance in production
6. Integrate ML solutions into APIs, microservices, and enterprise systems
7. Work with large datasets to ensure data quality, validation, and availability
8. Monitor models in production and implement retraining and performance tuning pipelines
9. Collaborate with cross-functional teams to translate business requirements into ML solutions
Experience Required
10. Strongmercial experience (typically 4–8+ years) in machine learning, data engineering, or software engineering
11. Proven experience deploying machine learning models into production environments
12. Strong hands-on experience with end-to-end ML pipelines (data ingestion → training → deployment → monitoring)
13. Experience implementing MLOps practices, including CI/CD pipelines and model life cycle management
14. Strong background in data processing and feature engineering
15. Experience working with large-scale datasets and distributed data systems
16. Experience integrating ML models into APIs, applications, and business systems
17. Solid understanding of model evaluation, optimisation, and performance tuning
18. Experience working in cloud environments (Azure, AWS, or GCP)
19. Proven ability to work in cross-functional agile teams
20. Previous contract or consulting experience in enterprise environments is highly desirable.
Key Skills
21. Python (essential)
22. ML frameworks (Scikit-learn, TensorFlow, PyTorch)
23. Data processing tools (Pandas, NumPy)
24. SQL / NoSQL databases
25. Cloud platforms (Azure, AWS, GCP)
26. Docker, Kubernetes (desirable)
27. CI/CD and DevOps tooling
Desirable Experience
28. Experience with real-time / streaming ML systems
29. Familiarity with Databricks, Spark, or big data platforms
30. Exposure to LLMs / Generative AI (RAG, embeddings, etc.)
31. Experience with feature stores and modern ML tooling (, Feast)
32. Knowledge of AIernance and model explainability
33. Industry experience in [Finance / Retail / Healthcare – tailor as needed]
What’s on Offer
34. Opportunity to work on high-impact machine learning projects
35. Collaborative and forward-thinking engineering environment
36. Flexible working arrangements
Apply NowIf you’re a skilled Machine Learning Engineer looking for your next contract and want to work on meaningful ML solutions, we’d love to hear from you. #4802431 - Ashley Sharp