Artificial Intelligence Engineer

Harnham
Manchester, United Kingdom
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
£ 80K

Job location

Remote
Manchester, United Kingdom

Tech stack

API
Artificial Intelligence
Airflow
Big Data
Continuous Integration
Python
Machine Learning
TensorFlow
Management of Software Versions
PyTorch
Large Language Models
Backend
Information Technology
HuggingFace
Machine Learning Operations

Job description

We're partnered with a fast-growing tech startup focused on how brands and retailers use data. Their AI platform brings together data science, immersive visualisation, and large-scale machine learning to optimise product ranges, plan shopper journeys, and drive smarter commercial decisions., * Design, build, and maintain scalable backend systems that power advanced ML and LLM applications.

  • Develop and manage end-to-end MLOps pipelines with automation, reproducibility, and scalability at their core.
  • Deploy and monitor machine learning and LLM models in production, identifying model drift and performance issues.
  • Drive research and development in modern ML, AI, and LLM approaches, applying SOTA techniques in a real-world setting.
  • Champion clean, maintainable, and well-documented code following best engineering practices.

Requirements

  • Strong academic background in Computer Science, ML, AI, or a related field.
  • Deep hands-on experience with Python and ML frameworks (PyTorch, TensorFlow, Hugging Face).
  • Proven background in MLOps, including model versioning, CI/CD for ML, and production monitoring.
  • Experience building robust backend systems and APIs to serve ML models at scale.
  • Strong understanding of big data technologies and data orchestration tools (Airflow, DBT).
  • Familiarity with LLM integration and optimisation in production environments.
  • Excellent problem-solving, analytical, and communication skills.
  • Experience fine-tuning LLMs (e.g. Unsloth, cloud-based methods).

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