Lead AI / ML Consultant

Lead AI/ML Consultant

Infinity Quest UK

London, E4 7FH

£46,704 per year - estimated ?

EASY APPLYNEW

Required Skills & Qualifications

• Python proficiency sufficient to build prototypes, review engineering output, and debug issues independently.


• Familiarity with orchestration frameworks: LangChain, Semantic Kernel, or Microsoft Prompt Flow.


• Hands-on experience with Microsoft Azure AI Foundry.


• Working knowledge of Azure DevOps or GitHub for managing AI experiment tracking and deployment pipelines.


• Ability to read and interpret SQL; experience with cloud data platforms (Databricks, Synapse, or equivalent) is advantageous.

Preferred Qualifications/Certifications

• Microsoft Certifications: AI-102 (Azure AI Engineer), DP-100 (Azure Data Scientist), AI-900, or equivalent.


• Familiarity with insurance-specific AI regulation guidance.


• Exposure to ML Ops practices: model versioning, drift detection, retraining pipelines, and A/B evaluation in production.


• Experience with multi-modal AI (document + image pipelines relevant to property claims or risk surveys).


• Familiarity with data bricks


• Prior experience in a vendor or consultancy environment managing multiple concurrent client engagements.


• Knowledge of CI/CD for Databricks (Azure DevOps, GitHub Actions).


• Exposure to data governance, security, and compliance frameworks.

#s1-Gen

Required Skills & Qualifications Python proficiency sufficient to build prototypes, review engineering output, and debug issues independently. Familiarity with orchestration frameworks: LangChain, Semantic Kernel, or Microsoft Prompt Flow. Hands-on experience with Microsoft Azure AI Foundry Working knowledge of Azure DevOps or GitHub for managing AI experiment tracking and deployment pipelines. Ability to read and interpret SQL; experience with cloud data platforms (Databricks, Synapse, or equivalent) is advantageous. Preferred Qualifications/Certifications Microsoft Certifications: AI-102 (Azure AI Engineer), DP-100 (Azure Data Scientist), AI-900, or equivalent. Familiarity with insurance-specific AI regulation guidance. Exposure to ML Ops practices: model versioning, drift detection, retraining pipelines, and A/B evaluation in production. Experience with multi-modal AI (document + image pipelines relevant to property claims or risk surveys). Familiarity with data bricks Prior experience
in a vendor or consultancy environment managing multiple concurrent client engagements. Knowledge of CI/CD for Databricks (Azure DevOps, GitHub Actions). Exposure to data governance, security, and compliance frameworks.