Machine Learning Engineer

We are seeking an experienced AI/ML Engineer with strong MLOps expertise to join one of our FinTech client’s team on a contract basis. You will play a pivotal role in taking AI models from proof-of-concept to robust production deployment, ensuring scalability, performance, and compliance.

Contract AI/ML Engineer (with MLOps)

Location: Remote (UK-based) or Hybrid – Client Site as Required

Contract Length: 6 months (extension likely)

Day Rate: £650–£850 (Outside IR35, subject to assessment)

Start Date: ASAP

This is a hands-on role for an engineer who thrives in fast-moving environments, working across data pipelines, model optimisation, cloud deployment, and continuous integration/monitoring.

Key Responsibilities

• Model Development: Build, train, and fine-tune machine learning models (including large language models and traditional ML).
• MLOps Implementation: Design and maintain CI/CD pipelines for ML, including automated training, testing, deployment, and rollback strategies.
• Data Pipeline Engineering: Develop and optimise data ingestion, transformation, and feature engineering processes.
• Production Deployment: Deploy models to cloud environments (AWS, Azure, or GCP) with a focus on scalability and reliability.
• Monitoring & Optimisation: Implement monitoring for model drift, performance, and cost-efficiency.
• Collaboration: Work closely with data scientists, engineers, and product managers to align model outputs with business requirements.
• Compliance: Ensure AI/ML systems adhere to relevant regulatory and ethical guidelines (EU AI Act, UK data privacy standards).

Required Skills & Experience

• Proven experience delivering ML models into production environments.
• Strong programming skills in Python (and familiarity with libraries such as PyTorch, TensorFlow, Scikit-learn).
• Experience with MLOps tools (MLflow, Kubeflow, Vertex AI, SageMaker, or similar).
• Proficiency with cloud platforms (AWS, Azure, or GCP).
• Strong background in data engineering (ETL, feature stores, SQL/NoSQL databases).
• Experience with containerisation & orchestration (Docker, Kubernetes).
• Knowledge of CI/CD best practices for ML.
• Strong communication skills, able to work effectively in a cross-functional team.

Nice to Have

• Experience with generative AI / LLMs in production.
• Knowledge of AI governance and compliance frameworks.
• Background in fintech, payments, or regulated industries.

Contract Details

• Day Rate: £650–£850 (Outside IR35, subject to determination)
• Location: Remote-first with occasional on-site meetings.
• Duration: 6 months (potential to extend)
• Start Date: ASAP

This role is perfect for an experienced AI/ML Engineer who has taken machine learning models from concept to live production in a business setting, and is comfortable managing the full process — from preparing the data, building and training the model, to deploying, monitoring, and improving it once it’s in use.