Description
We are seeking an AI Data Foundation Research Engineer to work on developing infrastructures and algorithms for capturing, managing, enhancing, and interpreting meta-data and lineage for AI pipelines.
The successful candidate will work on enabling reproducibility, reuse, and optimization of pipelines, search, discovery, selection, and usage of relevant high-quality data for trustworthy AI outcomes across multiple AI applications.
Responsibilities include:
- Developing, evaluating, and testing Foundation AI models for different modalities such as Natural Language Processing, Large Language Models, Time Series Analysis, and Computer Vision
- Augmenting AI models with structured knowledge through data and knowledge context retrieval, filtering, prioritization, advanced reasoning, and reasoning trace capture and validation
- Developing Agentic OS infrastructures to enable consistent management of context, reasoning, governance policies, and guardrails across different agentic harnesses
Requirements:
- PhD in Computer Science or related fields with a focus on data engineering and data science, particularly Machine Learning, Deep Learning, and/or data management for AI
- 3 years of relevant industry experience
Preferred skills:
- Research experience in Generative AI, Deep Learning, and Machine Learning
- Experience with advanced AI model architectures such as LLMs, Time Series Foundation Models, and Diffusion Models
- Expertise with end-to-end pipelines for AI and Machine Learning, particularly the data layer underlying the pipelines
- Experience in AI model development lifecycle, ML/deep learning frameworks, and MLOps platforms
- Strong programming skills in Python with high proficiency in data structures and algorithms