D
Drweng1mo ago

AI Engineer

United KingdomLondonmid
EngineeringData Science
0 views0 saves0 applied

Quick Summary

Key Responsibilities

Drive end-to-end development of AI infrastructure and AI driven applications: from initial proof-of-concept to production deployment and ongoing maintenance. Collaborate with technologists, traders,

Requirements Summary

Bachelor’s or advanced degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.

Technical Tools
EngineeringData Science

Key Responsibilities:

  • Drive end-to-end development of AI infrastructure and AI driven applications: from initial proof-of-concept to production deployment and ongoing maintenance.
  • Collaborate with technologists, traders, quantitative researchers, and data scientists to identify high-impact opportunities for integrating AI and machine learning into technology and business use cases.
  • Implement automated systems for continuous training, validation, and monitoring of models, minimizing downtime and ensuring reliability.
  • Provide technical leadership in selecting, integrating, and optimizing AI and ML frameworks, libraries, and tools across diverse hardware and software environments.
  • Create and maintain feature pipelines, feature stores, and model stores.
  • Develop frameworks to enable scalable, reproducible research.
  • Proactively troubleshoot performance bottlenecks, conduct root-cause analyses, and implement solutions to optimize GPU or CPU resource usage.

Qualifications:

  • Bachelor’s or advanced degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
  • 3+ years of experience working with machine learning and artificial intelligence technology.
  • Strong understanding of core machine learning and artificial intelligence concepts.
  • Excellent programming skills in Python.
  • Demonstrated experience in building, validating, deploying, monitoring, and updating production ML and AI models.
  • Hands-on experience with MLOps and AIOps infrastructure and tooling.
  • Proficient in problem-solving and analytical reasoning.
  • Exceptional communication and collaboration skills.
  • Experience with ML frameworks such as TensorFlow, PyTorch, TensorRT, or ONNX.
  • Experience with Large Language Models, including RAG and fine-tuning techniques.
  • Familiarity with compute infrastructure necessary to support operating AI and ML technology.

 

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Listing Details

Posted
February 27, 2026
First seen
March 26, 2026
Last seen
April 14, 2026

Posting Health

Days active
19
Repost count
0
Trust Level
39%
Scored at
April 14, 2026

Signal breakdown

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AI Engineer