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RTX Corporation

Data Scientist & Machine Learning Researcher

RTX Corporation

Published 10 May 2026
Gloucester, UK
Remote
Onsite

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Role Highlights

Languages used

Python

Key skills

ML Research
Machine Learning
Computer Vision
Data Science
Computer Science
LLMs
Generative AI
Mathematics
NLP
PhD
CD
Cloud
Agile

Tools, Libraries and Frameworks

HuggingFace
Docker
Linux
AWS
CLI
GCP
Azure
HTTP
Tensorflow
PyTorch

Description

The role involves developing novel artificial intelligence and machine learning solutions to address mission-focused problems. Responsibilities include scoping projects, conducting research, and performing technical development from initial concepts to final delivery. The individual will work within a team to propose new ideas and communicate technical approaches to senior leaders and stakeholders. The position requires contributing to both internal and customer-facing projects across a range of complex challenges.

Required Qualifications and Skills

Candidates are required to hold a BSc in Machine Learning, Data Science, Computer Science, Mathematics, or a related field. Essential experience includes coding in Python, utilizing ML packages, and delivering machine learning solutions to stakeholders. Applicants must demonstrate an understanding of AI and ML algorithms, including Generative AI, NLP, and computer vision, as well as experience training Large Language Models. Additionally, the role requires the ability to produce high-quality scientific writing and work with autonomy. A PhD or Master’s degree is considered a desirable qualification.

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

RTX Corporation

Size

125656

HQ

Arlington, US

Description

RTX is comprised of three market-leading businesses Collins Aerospace, Pratt & Whitney and Raytheon working as one to answer the biggest questions and solve the hardest problems in aerospace and defense.

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