Senior Machine Learning Engineer - £500 - Inside IR35 - London Hybrid

Summary: This role is for a Senior Machine Learning Engineer working on an AI/Machine Learning project within the insurance sector. The position requires strong Python engineering skills and experience in building production-quality AI/ML systems. The role is hybrid, requiring one day per week onsite in Central London, and is classified as inside IR35. The daily rate for this position is £500.

Key Responsibilities:

• Develop and maintain AI/ML systems for the insurance sector.
• Engage in technical discussions and build/debug code independently.
• Collaborate with data scientists, software engineers, and DevOps teams.
• Ensure production-quality standards through testing and validation.
• Design, build, and deploy machine learning or GenAI systems.
• Monitor and manage the lifecycle of machine learning models.

Key Skills:

• Strong commercial experience as a Machine Learning Engineer, ML Engineer, AI Engineer or Python-focused MLE.
• Excellent hands-on Python engineering skills, with strong fundamentals across OOP, async/concurrency, decorators, design patterns and clean code.
• Comfortable with Python-heavy technical discussions and building/debugging code without heavy reliance on AI tooling or Internet-based support.
• Experience building clean, well-tested, production-quality AI/ML systems.
• Experience designing, building and deploying machine learning or GenAI systems into production.
• Strong experience with testing, validation and Python unit testing, ideally using pytest.
• Experience with GenAI/LLMs, including RAG pipelines, embeddings, vector databases and agentic workflows.
• Ability to evaluate and compare different models or approaches, using relevant metrics and clear technical reasoning.
• Understanding of LLM application risks, including hallucination detection, output validation, prompt injection and jailbreak mitigation.
• Experience with MLOps, CI/CD, model monitoring, versioning and life cycle management.
• Good cloud, Docker and/or Kubernetes experience.
• Ability to work closely with data scientists, software engineers, DevOps teams and business stakeholders to deliver secure, production-ready AI systems.

Salary (Rate): £500 per day

City: Central London

Country: UK

Working Arrangements: hybrid

IR35 Status: inside IR35

Seniority Level: Senior

Industry: IT

Detailed Description From Employer:

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 £500 per day, inside IR35, and requires 1 day per week onsite in Central London.

Key Skills required:

• Strong commercial experience as a Machine Learning Engineer, ML Engineer, AI Engineer or Python-focused MLE.
• Excellent hands-on Python engineering skills, with strong fundamentals across OOP, async/concurrency, decorators, design patterns and clean code.
• Comfortable with Python-heavy technical discussions and building/debugging code without heavy reliance on AI tooling or Internet-based support.
• Experience building clean, well-tested, production-quality AI/ML systems.
• Experience designing, building and deploying machine learning or GenAI systems into production.
• Strong experience with testing, validation and Python unit testing, ideally using pytest.
• Experience with GenAI/LLMs, including RAG pipelines, embeddings, vector databases and agentic workflows.
• Ability to evaluate and compare different models or approaches, using relevant metrics and clear technical reasoning.
• Understanding of LLM application risks, including hallucination detection, output validation, prompt injection and jailbreak mitigation.
• Experience with MLOps, CI/CD, model monitoring, versioning and life cycle management.
• Good cloud, Docker and/or Kubernetes experience.
• Ability to work closely with data scientists, software engineers, DevOps teams and business stakeholders to deliver secure, production-ready AI systems.

If the above sounds like you, please apply now for immediate consideration.