At EY youll have the chance to build a career as unique as you are with the global scale support inclusive culture and technology to become the best version of you. And were counting on your unique voice and perspective to help EY become even better too. Join us and build an exceptional experience for yourself and a better working world for all.
AI Engineering
Role summary
You will engineer ship and operate AI powered services and APIs in production. The focus is on Python API development robust deployment practices and end to end MLOps/DevOps on AWS/Azure. Youll partner with data ML and platform teams to move models and AI capabilities from notebooks to reliable secure scalable services.
Key responsibilities
- Design build and operate production grade AI services/APIs owning reliability scalability and performance SLOs.
- Implement MLOps best practices (experiment tracking model packaging CI/CD for models automated testing feature and model registries telemetry) to reduce time to production.
- Drive DevOps automation (infrastructure as code containerization orchestration) and secure delivery with least privilege secrets management and policy-as-code.
- Lead deployment of AI components to AWS/Azure (containers serverless managed ML platforms) with strong observability and rollback plans.
- Collaborate cross functionally to translate product and analytics requirements into well designed APIs contracts and SLAs.
Must have skills
- MLOps (e.g. MLflow/Kubeflow/SageMaker/Azure ML) CI/CD for ML model registry monitoring
- DevOps (Docker Kubernetes IaCTerraform/Bicep GitHub/GitLab Actions/Azure DevOps)
- Python (production code quality testing packaging)
- Deployment to AWS/Azure (EKS/AKS ECS/Fargate Lambda/Functions API Gateway/App Gateway)
- API development (FastAPI/Flask OpenAPI/Swagger authN/Z rate limiting versioning)
Good to have
- GenAI/Agentic concepts vector databases prompt engineering fundamentals
Qualifications & experience
- in CS/EE or equivalent.
- 4 years in AI Engineering
EY Building a better working world
EY exists to build a better working world helping to create long-term value for clients people and society and build trust in the capital markets.
Enabled by data and technology diverse EY teams in over 150 countries provide trust through assurance and help clients grow transform and operate.
Working across assurance consulting law strategy tax and transactions EY teams ask better questions to find new answers for the complex issues facing our world today.
At EY youll have the chance to build a career as unique as you are with the global scale support inclusive culture and technology to become the best version of you. And were counting on your unique voice and perspective to help EY become even better too. Join us and build an exceptional experience f...
At EY youll have the chance to build a career as unique as you are with the global scale support inclusive culture and technology to become the best version of you. And were counting on your unique voice and perspective to help EY become even better too. Join us and build an exceptional experience for yourself and a better working world for all.
AI Engineering
Role summary
You will engineer ship and operate AI powered services and APIs in production. The focus is on Python API development robust deployment practices and end to end MLOps/DevOps on AWS/Azure. Youll partner with data ML and platform teams to move models and AI capabilities from notebooks to reliable secure scalable services.
Key responsibilities
- Design build and operate production grade AI services/APIs owning reliability scalability and performance SLOs.
- Implement MLOps best practices (experiment tracking model packaging CI/CD for models automated testing feature and model registries telemetry) to reduce time to production.
- Drive DevOps automation (infrastructure as code containerization orchestration) and secure delivery with least privilege secrets management and policy-as-code.
- Lead deployment of AI components to AWS/Azure (containers serverless managed ML platforms) with strong observability and rollback plans.
- Collaborate cross functionally to translate product and analytics requirements into well designed APIs contracts and SLAs.
Must have skills
- MLOps (e.g. MLflow/Kubeflow/SageMaker/Azure ML) CI/CD for ML model registry monitoring
- DevOps (Docker Kubernetes IaCTerraform/Bicep GitHub/GitLab Actions/Azure DevOps)
- Python (production code quality testing packaging)
- Deployment to AWS/Azure (EKS/AKS ECS/Fargate Lambda/Functions API Gateway/App Gateway)
- API development (FastAPI/Flask OpenAPI/Swagger authN/Z rate limiting versioning)
Good to have
- GenAI/Agentic concepts vector databases prompt engineering fundamentals
Qualifications & experience
- in CS/EE or equivalent.
- 4 years in AI Engineering
EY Building a better working world
EY exists to build a better working world helping to create long-term value for clients people and society and build trust in the capital markets.
Enabled by data and technology diverse EY teams in over 150 countries provide trust through assurance and help clients grow transform and operate.
Working across assurance consulting law strategy tax and transactions EY teams ask better questions to find new answers for the complex issues facing our world today.
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