AI Data Foundation Research Engineer (AI)

TL;DR

AI Data Foundation Research Engineer (AI): Developing new methods for context discovery, retrieval, and agentic AI workflows with an accent on multi-modal data representation and advanced reasoning. Focus on building high-quality data pipelines for trustworthy AI outcomes and evaluating Foundation AI models across NLP, Computer Vision, and Time Series.

Location: Hybrid: Average 2 days per week from an HPE office (USA)

Salary: USD 126,500 - 240,500 per year

Company

Global edge-to-cloud company advancing the way people connect, protect, and analyze their data and applications.

What you will do

• Develop new methods for context discovery, retrieval, filtering, and reasoning trace validation in agentic AI workflows.
• Build systems for the capture, management, and interpretation of meta-data and lineage for AI pipelines to enable reproducibility and optimization.
• Develop, evaluate, and test Foundation AI models for various modalities, including NLP, LLM, Time Series Analysis, and Computer Vision.
• Augment AI models with structured knowledge using knowledge-infused learning.
• Collaborate with internal software development teams and external partners to translate research into practical applications.

Requirements

• PhD in Computer Science or related fields focusing on data engineering, data science, Machine Learning, or Deep Learning.
• 3+ years of relevant industry experience.
• Experience with advanced AI architectures such as LLMs, Time Series Foundation Models, and Diffusion Models.
• Expertise in end-to-end AI/ML pipelines and data layers (e.g., DVC, Pachyderm).
• Experience with MLOps platforms (e.g., Pytorch/Tensorflow, MLFlow, Kubeflow, Ray).
• Experience with agentic AI platforms (e.g., LangGraph, CrewAI, LlamaIndex).

Nice to have

• High proficiency in Python (data structures/algorithms) and C/C++.
• Experience with CI/CD, Kubernetes, and containerized orchestration tools.
• Experience with hybrid AI-HPC workflows and knowledge graphs.
• Skills in multi-threaded programming, parallel processing, and distributed programming.

Culture & Benefits

• Comprehensive suite of health, financial, and emotional wellbeing benefits.
• Specific professional development programs to help reach career goals and knowledge expertise.
• Unconditionally inclusive environment that celebrates individual uniqueness.
• Flexibility to manage work and personal needs within a global team structure.