Lead Machine Learning Engineer - £575 - Inside IR35 - London Hybrid
Posted 7 days ago by RecOps
£575 Per day
Inside
Hybrid
Central London, UK
Summary: This role involves supporting an AI/Machine Learning project for a leading consultancy in the insurance sector. The position requires a Lead Machine Learning Engineer with strong technical leadership and hands-on Python engineering skills. The role is based in Central London, requires one day per week onsite, and is classified as inside IR35. The daily rate for this position is £575.
Key Responsibilities:
- Lead the development and deployment of AI/ML systems.
- Design and build clean, well-tested, production-quality AI/ML systems from scratch.
- Manage the life cycle of ML/AI models in secure production environments.
- Collaborate with data scientists, software engineers, and DevOps teams.
- Lead technical direction while remaining hands-on with coding.
- Build automated ML pipelines across training, testing, deployment, and monitoring.
Key Skills:
- Strong experience as a Lead Machine Learning Engineer or Senior MLE.
- Excellent hands-on Python engineering skills.
- Experience with testing, validation, TDD, and Python unit testing.
- Strong GenAI/LLM experience, including RAG pipelines and model evaluation.
- Understanding of LLM application risks and mitigation strategies.
- Good cloud, Docker, and/or Kubernetes experience.
- Strong understanding of MLOps, CI/CD, and model versioning.
Salary (Rate): £575 per day
City: Central London
Country: UK
Working Arrangements: hybrid
IR35 Status: inside IR35
Seniority Level: Senior
Industry: IT
RecOps is partnered with a leading consultancy to support an AI/Machine Learning project for one of their end clients in the insurance sector.
This role is £575 per day, inside IR35, and requires 1 day per week onsite in Central London.
Key Skills required:
- Strong experience as a Lead Machine Learning Engineer, Lead ML Engineer or Senior MLE with technical leadership experience.
- Excellent hands-on Python engineering skills, with strong fundamentals across OOP, async/concurrency, decorators, design patterns and production coding standards.
- Comfortable building and debugging Python systems without heavy reliance on AI tooling, frameworks or Internet-based support.
- Experience designing and building clean, well-tested, production-quality AI/ML systems from scratch.
- Strong experience with testing, validation, TDD and Python unit testing, ideally using pytest.
- Experience leading the deployment and life cycle management of ML/AI models in secure or restricted production environments.
- Strong GenAI/LLM experience, including RAG pipelines, embeddings, vector databases, agentic workflows and model evaluation.
- Ability to compare models and approaches, explain trade-offs, and choose the right model/architecture for the use case.
- Understanding of LLM application risks, including hallucination detection, output validation, prompt injection and jailbreak mitigation.
- Experience building automated ML pipelines across training, testing, deployment, monitoring and rollback.
- Strong understanding of MLOps, CI/CD, model versioning, experiment tracking and production observability.
- Good cloud, Docker and/or Kubernetes experience.
- Ability to lead technical direction while remaining hands-on with code, working closely with data scientists, software engineers, DevOps teams and stakeholders.
If the above sounds like you, please apply now for immediate consideration.