AI Research Engineer: Scale LLMs & Generative Models

US Tech Solutions; Greater London; On-site; GBP 73,000 - 79,000; Full time

Job summary

US Tech Solutions is seeking a Research Engineer to join a leading AI Research team focused on advancing AI, machine learning systems, and large language models. You’ll work on challenging AI problems, develop scalable research solutions, run experiments with large models and datasets, and collaborate with research and engineering teams.

Responsibilities include turning research findings into practical product insights, producing production‑quality code, and contributing to AI product innovation

Qualifications

• 2+ years of experience in Machine Learning, AI, Recommendation Systems, Pattern Recognition, or Data Mining.
• Hands-on experience with PyTorch or similar ML frameworks.
• Experience working with large-scale ML models and datasets.
• Experience with LLMs, Generative AI, model evaluation, or post-training.
• Bachelor’s degree in computer science, Computer Engineering, AI/ML, or related field, or equivalent experience.

Responsibilities

• Conduct research in AI and Machine Learning.
• Develop methods, tools, and infrastructure for LLMs.
• Build and evaluate machine learning models at scale.
• Run experiments using large AI models and datasets.
• Work on LLM querying, evaluation, and post-training.
• Collaborate with researchers and engineering teams.
• Convert research findings into practical product/business insights.
• Develop production-quality code alongside engineering teams.
• Contribute to research publications and AI product innovation.

Skills

Machine Learning

PyTorch

LLMs

Python

AI Research

Large Datasets

Recommendation Systems

Data Mining

Pattern Recognition

Education

Bachelor's in CS/CE/AI or related field

Tools

PyTorch (ML framework)

Job description

US Tech Solutions is seeking a Research Engineer to join a leading AI Research team focused on advancing AI, machine learning systems, and large language models. You’ll work on challenging AI problems, develop scalable research solutions, run experiments with large models and datasets, and collaborate with research and engineering teams.

Responsibilities include turning research findings into practical product insights, producing production‑quality code, and contributing to AI product innovation