Lead/Senior Machine Learning Engineer - £500 - £575 - Inside IR35 - London Hybrid

Summary: This role involves supporting an AI/Machine Learning project for a leading consultancy in the insurance sector. The position requires strong expertise in machine learning and Python engineering, with a focus on building production-quality AI systems. The role is based in Central London and requires one day per week onsite. It is classified as inside IR35 with a daily rate of £500.

Key Responsibilities:

• Support AI/Machine Learning projects for clients in the insurance sector.
• Build and debug production-quality AI/ML systems with minimal reliance on AI tooling.
• Collaborate with data scientists, software engineers, and business stakeholders.
• Design, build, and deploy machine learning or GenAI systems into production.
• Conduct testing, validation, and unit testing of AI systems.
• Evaluate and compare different models or approaches using relevant metrics.
• Manage MLOps, CI/CD, model monitoring, and lifecycle management.

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 lifecycle 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.