Microsoft Creative Technology is looking to engineer AI infrastructure and invent new ways to apply emerging AI techniques to diverse research challenges, turning cutting-edge research into reproducible, human-impact prototypes.
Requirements
- 2+ years of experience building production grade AI pipelines on Azure, AWS, or GCP.
- Familiarity with one or multiple of the following technologies: state-of-the-art AI/ML systems, generative AI, cloud computing, real-time graphics, XR, computational media and/or creative and media tools.
- Advanced proficiency in one or multiple technologies: Azure, Python, React TS, NoSQL, Cosmos DB, .NET, and AI technologies such as Large Language Models (LLMs), semantic embeddings, search, and/or RAG (Retrieval-Augmented Generation).
- Demonstrated ability to build creative AI prototypes, supported by a portfolio of open-source projects, hackathon work, publications, or other innovative contributions.
- Demonstrated experience building, integrating, or extending media, creative, or visualization tools (e.g., video, audio, 3D, interactive experiences).
- Experience designing scalable, responsible AI solutions with considerations for bias mitigation, privacy, sustainability, and diverse user needs.
- Experience with generative diffusion, large language models, federated learning, quantumML, or neuromorphic hardware.
Responsibilities
- Design, deploy, and maintain a shared AzureML workspace, Graphics Processing Unit (GPU)/Tensor Processing Unit (TPU) pools, and prototype applications that build on state of the art research.
- Create modular, “press‑run‑model” Software Development Kit (SDKs) that let researchers and developers invoke sophisticated AI (e.g., Computer Use Agents, federated learning, RAG, diffusion) with a single line of code.
- Prototype emerging AI paradigms (prompt‑engineering, retrieval‑augmented generation, generative diffusion, quantum‑ML hybrids) and evaluate their suitability for research pilots.
- Engineer data pipelines for synthetic data generation, privacy‑preserving transformations, and playful data‑augmentation strategies.
- Build interactive AI “playgrounds” (notebooks, visual dashboards, chat‑style explorers) that surface model behaviour, trade‑offs, and storytelling potential.
- Optimize models for latency, cost, and edge‑device constraints while preserving the narrative fidelity of the output.
- Document workflows, version‑control models, and publish reusable patterns for the broader research and developer community.
Other
- Embody our culture and values.
- Collaborate in design‑research workshops and ideation sessions, proposing AI‑centric narrative arcs that elevate the prototype’s impact.
- Passion for creativity and scientific inquiry, with experience leading hypothesis-driven research, applying data-driven methodologies, and validating concepts through experimentation and strategic analysis.
- Proven scientific communication skills, demonstrated through publications, patents, open-source contributions, and the ability to clearly document and present technical work to diverse audiences.
- Experience working at the intersection of research and development, innovation-focused, or creative technology teams.
