SC Cleared AI/ML Engineer
Posted 7 days ago by IO Associates
£650 Per day
Undetermined
Hybrid
London, UK
Summary: The role of Machine Learning & AI Specialist involves transforming machine learning concepts into functional products within a rapidly scaling enterprise. This position emphasizes practical deployment over academic research, focusing on delivering robust models that address operational challenges. The specialist will work closely with data architecture, cloud infrastructure, and predictive modeling to drive revenue. The role offers flexibility with fully remote or hybrid working arrangements in the UK.
Key Responsibilities:
- Architect, train, and launch production-grade artificial intelligence and machine learning applications.
- Own the end-to-end development cycle, from raw data ingestion to model deployment and runtime optimisation.
- Adapt, fine-tune, and embed Large Language Models (LLMs) directly into corporate operational workflows.
- Partner with infrastructure and data engineering squads to scale and produce machine learning codes.
- Construct resilient data pipelines and secure APIs to feed downstream AI services.
- Advise on high-level architecture across both machine learning stacks and cloud systems.
Key Skills:
- Demonstrated track record of shipping and maintaining live ML/AI software in commercial environments.
- Advanced proficiency in Python alongside deep learning ecosystems like PyTorch or TensorFlow.
- Hands-on engineering experience within major cloud platforms (AWS, Azure, or GCP).
- Deep understanding of core data engineering methodologies and automated pipeline design.
- Practical experience leveraging Generative AI technologies, including Retrieval-Augmented Generation (RAG), prompt optimization, and model fine-tuning.
- Thrives in high-velocity, output-oriented engineering cultures.
Salary (Rate): £650 per day
City: London
Country: UK
Working Arrangements: hybrid
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Machine Learning & AI Specialist
Arrangement: Fully Remote (UK-wide) or Hybrid (London or Manchester hubs)
Term: 6-Month Contract
Compensation: Competitive daily rate, performance bonus, plus comprehensive benefits package
Overview
A rapidly scaling enterprise is looking for a delivery-focused engineer to turn machine learning concepts into functional, revenue-driving products. This is a practical deployment role rather than an academic research position; the focus is entirely on shipping robust models that solve concrete operational challenges. You will bridge the gap between data architecture, cloud infrastructure, and predictive modelling.
Core ResponsibilitiesArchitect, train, and launch production-grade artificial intelligence and machine learning applications.
Own the end-to-end development cycle, from raw data ingestion to model deployment and runtime optimisation.
Adapt, fine-tune, and embed Large Language Models (LLMs) directly into corporate operational workflows.
Partner with infrastructure and data engineering squads to scale and produce machine learning codes.
Construct resilient data pipelines and secure APIs to feed downstream AI services.
Advise on high-level architecture across both machine learning stacks and cloud systems.
Required Technical Background
Demonstrated track record of shipping and maintaining live ML/AI software in commercial environments.
Advanced proficiency in Python alongside deep learning ecosystems like PyTorch or TensorFlow.
Hands-on engineering experience within major cloud platforms (AWS, Azure, or GCP).
Deep understanding of core data engineering methodologies and automated pipeline design.
Practical experience leveraging Generative AI technologies, including Retrieval-Augmented Generation (RAG), prompt optimization, and model fine-tuning.
Thrives in high-velocity, output-oriented engineering cultures.
Preferred Extras
Familiarity with MLOps frameworks, including continuous integration/deployment (CI/CD) for models, version control, and drift monitoring.
Working knowledge of embeddings and vector storage solutions.
Background in developing micro services and Back End API architectures.
Prior experience in external consulting or stakeholder-facing engineering roles.
What Makes This Unique
Tangible Output: Focus on building applications that go live, avoiding dead-end R&D loops.
High Autonomy: Direct influence over how advanced computing technologies are adopted across an expanding organisation.
Execution Culture: Work alongside an agile team structured entirely around speed-to-market and measurable impact.
