AI/ML Engineer | Contract | London
Myn Corporate
London, United Kingdom
Duration
6
MONTHS
Negotiable
Ref
myn-corporate-132603
Starts
ASAP
Opened On
08/10/2026
Required Skills
ml production experience
python proficiency
deep learning frameworks
mlops experience
cloud platforms
container orchestration
generative ai
data engineering tools
ai governance
Job Description
We're recruiting an experienced AI/ML Engineer for a contract role designing, building and deploying machine learning and generative AI solutions into production. You'll take models from prototype to reliable, scalable services, working closely with data scientists, product and platform engineers to deliver measurable business impact.
Location: London, UK
Day rate: £650–£750 per day (IR35 status to be confirmed)
Contract: Initial 6–12 months, likely extension
What you'll do:
- Design, build, train and evaluate ML models and LLM/GenAI applications
- Productionise models as scalable inference services and APIs
- Develop data and feature pipelines with data engineering teams
- Build and optimise RAG pipelines, prompt workflows, agents and fine-tuned models
- Implement MLOps, including experiment tracking, model versioning, CI/CD for ML and drift monitoring
- Deploy ML workloads on AWS, Azure or GCP using Docker and Kubernetes
- Apply responsible AI practices, including bias testing, explainability and UK GDPR compliance
What you'll bring:
- Degree in Computer Science, Machine Learning, Mathematics, Engineering or similar; MSc/PhD an advantage
- 3–6 years' experience deploying ML systems in production
- Strong Python skills with PyTorch, TensorFlow or scikit-learn, plus pandas and NumPy
- Hands-on MLOps experience (MLflow, Kubeflow, SageMaker, Vertex AI or Azure ML)
- Cloud, container and CI/CD experience
- Solid grounding in model evaluation, statistics and experimentation
- Right to work in the UK
Desirable: LLMs and generative AI, including RAG, vector databases and fine-tuning; NLP, computer vision, time series or recommender systems; Spark, dbt, Airflow, Snowflake or Databricks; regulated environments.