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IBM

AI Foundations - Research Software Engineer

IBM

Published 14 May 2026
Cambridge, MA, USA
Full Time

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Role Highlights

Languages used

Rust
C++

Key skills

foundation model
LLMs
Research
AI
Cloud
Compilers
Transformers
Data

Tools, Libraries and Frameworks

IOS
IBM
GPUs

Description

The role involves building the future of the open model weight ecosystem through foundation model and software harness co-design. The individual will bridge the gap between theoretical research and practical application by developing software and model capabilities for small and medium-sized models. Responsibilities include collaborating with scientists and academic partners to advance open AI initiatives. The position requires working on low-level systems code and contributing to the development of novel training regimes. The successful candidate will publish research that supports the open weight community.

Required Qualifications and Skills

The role requires expertise in compilers, programming languages, or related fields such as formal verification and theorem proving. Candidates must demonstrate proficiency in systems programming languages, specifically Rust or C++. Additionally, the ability to rapidly prototype, build, and iterate on software projects is necessary. Experience with Transformer architectures, Large Language Models, data pipelines, and GPU programming is considered beneficial.

Disclaimer

Disclaimer: Job and company description information and some of the data fields may have been generated via GPT-4 summarisation and could contain inaccuracies. The full external job listing link should always be relied on for authoritative information.

About the company

IBM

Size

305978

Website

ibm.com

HQ

Armonk, New York, US

Public/Private

Public Company

Description

IBM infuses core business operations with intelligence, from machine learning to generative AI, to make organizations more responsive, productive, and resilient. It helps clients put AI into action now, creating real value with trust, speed, and confidence across various areas like digital labor, IT automation, and security. The ability to utilize all data is critical, as AI's effectiveness is dependent on the quality of data fueling it, with IBM's AI, and data platform aiming to scale and accelerate AI's impact with trusted data. IBM's hybrid cloud platform offers a comprehensive approach to development, security, and operations across hybrid environments, laying a flexible foundation for leveraging data wherever it resides.

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