Lead Machine Learning Engineer, Associate Director (London)
Tasks
- Build data pipelines for ETL
- Build scalable ML and gen AI workflows
- Collaborate with data scientists on ML solutions
- Communicate ML concepts to business stakeholders
- Create AI engineering standards and recommendations
- Create performance metrics for ML solutions
- Design and develop AI agents
- Develop and deploy MLOps platforms
- Develop and deploy production machine learning systems
- Evaluate vendors and tools for AI solutions
- Implement generative AI and machine learning solutions
- Maintain production SLAs for AI applications
- Orchestrate large scale data workflows
- Support AI governance policies
Perks/Benefits
- N/A
Skills/Tech-stack
AI Search | AWS | AWS Bedrock | AWS S3 | AWS SageMaker | Agent systems | Agentic AI | Apache Airflow | Automated testing | Azure | Azure AI | Azure AI Search | Azure Blob | Azure Blob Storage | Azure OpenAI | Blob Storage | Data orchestration | Decision Trees | Deep learning | Docker | ETL | Generative AI | Information Retrieval | Java | Kubernetes | Language Models | Language Processing | Large Language Models | Machine Learning | Multi-Agent | Multi-Agent Systems | Multi-class classification | Natural Language | Natural Language Processing | Neural Networks | Python | Search | Source Control | Support Vector Machines | Vector machines
Education
Bachelor of Science | Master of Engineering | Master of Science | PhD
Roles
AI | AI Engineer | Data Scientist | Engineer | Learning Engineer | MLOps Engineer | Machine Learning Engineer | Scientist
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