About This Role
We're seeking a passionate Generative AI Engineer and problem solver with deep Azure Cloud expertise to join our world-class team of innovators who are pushing the boundaries of what's possible with artificial intelligence. You'll be at the forefront of cutting-edge AI research and development, working on impactful projects that leverage Azure AI and Machine Learning services to deliver scalable, production-grade solutions.
Core Responsibilities:
- Collaborate with cross-functional teams to translate complex AI concepts into practical, deployable business solutions.
- Design and implement systems using both open-source and enterprise-grade models (e.g., Llama, Gemini, GPT) to solve innovative problems.
- Build robust evaluation pipelines to assess model performance, safety, and alignment with business objectives.
- Optimize model latency, scalability, and cost-efficiency for large-scale Azure-based deployments.
- Architect cloud-native ML infrastructure using Azure Machine Learning (Azure ML), AI Foundry, and related Azure AI services.
- Fine-tune and serve Large Language Models (LLMs) and transformer-based architectures using Azure's compute and MLOps ecosystem.
- Implement end-to-end MLOps pipelines leveraging Azure DevOps, MLflow, and CI/CD best practices.
- Integrate AI capabilities into enterprise applications using Azure OpenAI Service, Azure Cognitive Search, and Azure AI Studio.
- Effectively communicate complex AI concepts to both technical and non-technical stakeholders.
Experience Requirements:
- 6+ years of overall experience in data science, machine learning, or AI engineering.
- 1.5+ years of hands-on experience with Generative AI and LLMs.
- Proven experience in Azure Cloud, including Azure Machine Learning, AI Foundry, Azure OpenAI, and Azure Cognitive Services.
- Strong background in deploying ML/DL models to production using Azure MLOps pipelines.
- Advanced degree in Computer Science, Machine Learning, or a related field preferred.
