About the position
To design, build, deploy and support Machine Learning, AI and Generative AI solutions in production.
The role will focus on turning AI/ML models and prototypes into scalable, reliable and business-ready solutions.
Key Responsibilities
- Build and deploy Machine Learning and AI solutions into production.
- Develop ML pipelines using Databricks and MLflow.
- Build GenAI, LLM, RAG and AI Agent solutions.
- Deploy AI/ML solutions on Azure and AKS.
- Develop APIs and microservices for AI/ML applications.
- Use Docker and Kubernetes for scalable deployments.
- Implement MLOps, CI/CD, testing and monitoring.
- Monitor, troubleshoot and optimize production AI/ML solutions.
- Work with Data Scientists to move models from development into production.
- Collaborate with Cloud, Infrastructure, Security and Technology teams.
- Mentor junior engineers and contribute to best practices.
Key Deliverables
- Production-ready ML models and pipelines.
- Deployed GenAI, LLM, RAG and AI Agent solutions.
- AI/ML applications and APIs running on Azure/AKS.
- Automated deployment, testing and monitoring processes.
- Secure, scalable and reliable AI/ML solutions.
Requirements - Relevant degree in Computer Science, Engineering, Data Science, Econometrics, Mathematical Statistics, Actuarial Science or a related field.
- Senior-level experience in Machine Learning Engineering, AI Engineering, MLOps or a related technical role.
- Proven experience deploying and supporting AI/ML solutions in production.
- Strong experience with Python.
- Hands-on experience with Databricks and MLflow.
- Experience with Azure and AKS.
- Experience with Docker and Kubernetes.
- Experience with MLOps and CI/CD.
- Experience with Generative AI, LLMs, RAG and/or AI Agents.
- Experience developing REST APIs and microservices.
Desired Skills:
- Python
- Databricks
- MLFlow
- MLOps
- CI/CD
- Azure
- AKS
Desired Qualification Level:
About The Employer: