Machine Learning Engineer

Edison Smart®; Remote; GBP 125,000 - 150,000; Part time

Job summary

A leading technology firm is seeking an experienced Machine Learning Engineer for a 6-month contract to support a Financial Services organization. The role includes designing and deploying ML models in production and requires strong Python and ML library skills. Ideal candidates will have experience within regulated environments and a deep understanding of MLOps practices. This position offers a competitive daily rate and opportunities for contract extension. Remote work is available.

Qualifications

• Proven commercial experience as a Machine Learning Engineer, ideally within Financial Services or a regulated environment.
• Hands-on experience with ML libraries such as TensorFlow, PyTorch, and scikit-learn.
• Experience deploying and supporting ML models in production.

Responsibilities

• Design, build, and deploy machine learning models into production.
• Collaborate closely with Data Scientists and Software Engineers.
• Build and maintain end-to-end ML pipelines.

Skills

Python

TensorFlow

PyTorch

scikit-learn

MLOps best practices

Cloud platforms (AWS, GCP, Azure)

Tools

Docker

Kubernetes

MLflow

Kubeflow

Airflow

Job description

Machine Learning Engineer - Contract (Financial Services, Outside IR35)

Duration: 6 months

Rate: £650 - £750 per day

IR35: Outside

Location: UK / Remote

We’re seeking an experienced Machine Learning Engineer to support a Financial Services organisation on an initial 6-month contract, working on production‑grade ML systems that operate in regulated, high‑volume environments.

This role is ideal for someone comfortable taking models from research through to deployment, with a strong appreciation for robust engineering, governance, and scalability.

Responsibilities

• Design, build, and deploy machine learning models into production within a Financial Services environment
• Collaborate closely with Data Scientists, Software Engineers, Risk, and Product teams
• Build and maintain end‑to‑end ML pipelines (training, validation, inference, monitoring)
• Ensure models meet requirements around performance, resilience, and explainability
• Contribute to MLOps best practices, model governance, and technical standards
• Support model monitoring, drift detection, and ongoing optimisation

Required Experience

• Proven commercial experience as a Machine Learning Engineer, ideally within Financial Services, FinTech, or a regulated environment
• Strong Python skills and hands‑on experience with ML libraries (TensorFlow, PyTorch, scikit‑learn)
• Experience deploying and supporting ML models in production
• Solid understanding of data pipelines, versioning, testing, and software engineering best practices
• Experience working with cloud platforms (AWS, GCP, or Azure)

Nice to Have

• Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases
• Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.)
• Docker and Kubernetes experience
• Exposure to model governance, explainability, or regulatory frameworks

Contract Details

• £650–£750 per day (Outside IR35)
• Initial 6-month contract, with strong extension potential
• Immediate or short‑notice start preferred