MLops Engineer

Join us as an AI Engineer within the AI Engineering division of DAAS (Data, AI & Automation Services), specializing in Azure, AWS, and OpenShift/Azure ML DevOps. In this role, you'll:

Collaborate with different teams to propose AI solutions on different use cases across the insurance value chain, with a focus on AIops and MLOps

Research, build, and deploy AI models as part of the broader AI team, leveraging AIops and MLOps practices for efficient model management

Contribute to our DevOps practices using OpenShift or Azure ML DevOps

If you're an intermediate enthusiast in the field of AI and passionate about exploring AI use cases in insurance, seize this opportunity to join us and make a significant impact.

Technical skills:

Expertise is required in the following fields:

Implementation of at least 5 AI projects, preferably with experience in AIOps and MLOps

Experience with Azure, OpenShift, Databricks, MLFlow

DevOps for model deployment, monitoring, and management

Setting up CI/CD pipelines using Azure DevOps, Jenkins, etc.

Hands-on experience with Generative AI tech LLMs, RAG, Prompt Engineering

Broad understanding of machine learning algorithms and techniques, including LLMs/SLMs, supervised/unsupervised algorithms, agentic ai

Soft skills:

Work collaboratively with broader Data and Tech teams, along with global multi-lingual teams.

Communicate effectively with non-technical stakeholders for collecting requirements, communicating deliverables, value generated, challenges.

Background and experience:

4-9 years of progressive experience in AI and ML, with a focus on AIops and MLOps

Experience in deploying and managing AI models in production environments using Databricks, MLFlow, Azure ML.