Microsoft Dynamics 365 is looking to solve business needs through AI/ML solutions, specifically in sales, marketing, and contact center operations, to deliver unparalleled customer experiences.
Requirements
- 1+ year(s) of experience building generative AI applications
- 2+ years of experience contributing to the design and implementation of model finetuning pipelines (e.g., LoRA, domain/task-specific adaptation) for customer and product scenarios
- 2+ years of applying transformer architectures and reinforcement learning techniques to improve finetuned models for reasoning, search, and generation tasks
- Deep expertise in designing and scaling Generative AI pipelines (e.g., RAG systems, domain/task-specific finetuning)
- Experience with Large Language Models (LLM)
- Experience with AI/ML solutions and software development
- Experience with data modeling or data engineering work
Responsibilities
- Implement AI/ML solutions to solve business needs
- Implement AI features towards a wide variety of business problems within Dynamics 365 products portfolio
- Ensure AI features are done to meet rigorous quality standards
- Develop extensive knowledge in the domain and technical framework, notably in Large Language Models (LLM)
- Assess business needs and integrate research to achieve business objectives
- Design, measure, and build AI applications to drive tangible business results
- Assess the effectiveness of models and collaborate with product teams to design AI-driven experiences and build AI agents
Other
- Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 2+ years experience in business analytics, data science, software development, data modeling or data engineering work
- Ability to meet Microsoft, customer and/or government security screening requirements
- Ability to work onsite 3 days a week in Microsoft's offices in Redmond, WA
- Must pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter
- Must be able to collaborate with a team of skilled applied scientists and software engineers
