Duration: Initial 6 months (with strong extension potential)

About the Role

We’re working with a leading organisation seeking a skilled Machine Learning Engineer to support the development and deployment of scalable ML solutions.

This is a hands-on contract role, ideal for someone who can take models from concept to production, working closely with data scientists, engineers, and stakeholders to deliver high-impact machine learning capabilities.

Key Responsibilities

• Design, build, and deploy production-grade machine learning models
• Develop and maintain data pipelines and feature engineering workflows
• Collaborate with data scientists to operationalise models and improve performance
• Implement MLOps best practices, including CI/CD, monitoring, and versioning
• Optimise models for scalability, reliability, and performance in production
• Integrate ML solutions into APIs, microservices, and enterprise systems
• Work with large datasets to ensure data quality, validation, and availability
• Monitor models in production and implement retraining and performance tuning pipelines
• Collaborate with cross-functional teams to translate business requirements into ML solutions

Experience Required

• Strong commercial experience (typically 4-8+ years) in machine learning, data engineering, or software engineering
• Proven experience deploying machine learning models into production environments
• Strong hands-on experience with end-to-end ML pipelines (data ingestion * training * deployment * monitoring)
• Experience implementing MLOps practices, including CI/CD pipelines and model life cycle management
• Strong background in data processing and feature engineering
• Experience working with large-scale datasets and distributed data systems
• Experience integrating ML models into APIs, applications, and business systems
• Solid understanding of model evaluation, optimisation, and performance tuning
• Experience working in cloud environments (Azure, AWS, or GCP)
• Proven ability to work in cross-functional agile teams
• Previous contract or consulting experience in enterprise environments is highly desirable.

Key Skills

• Python (essential)
• ML frameworks (Scikit-learn, TensorFlow, PyTorch)
• Data processing tools (Pandas, NumPy)
• SQL / NoSQL databases
• Cloud platforms (Azure, AWS, GCP)
• Docker, Kubernetes (desirable)
• CI/CD and DevOps tooling

Desirable Experience

• Experience with real-time / streaming ML systems
• Familiarity with Databricks, Spark, or big data platforms
• Exposure to LLMs / Generative AI (RAG, embeddings, etc.)
• Experience with feature stores and modern ML tooling (e.g., Feast)
• Knowledge of AI governance and model explainability
• Industry experience in [Finance / Retail / Healthcare - tailor as needed]

What’s on Offer

• Opportunity to work on high-impact machine learning projects
• Collaborative and forward-thinking engineering environment
• Flexible working arrangements
• Competitive day rate with extension potential

Apply Now

If you’re a skilled Machine Learning Engineer looking for your next contract and want to work on meaningful ML solutions, we’d love to hear from you.

4802431 - Ashley

• Strong commercial experience (typically 4-8+ years) in machine learning, data engineering, or software engineering
• Proven experience deploying machine learning models into production environments
• Strong hands-on experience with end-to-end ML pipelines (data ingestion * training * deployment * monitoring)
• Experience implementing MLOps practices, including CI/CD pipelines and model life cycle management
• Strong background in data processing and feature engineering
• Experience working with large-scale datasets and distributed data systems
• Experience integrating ML models into APIs, applications, and business systems
• Solid understanding of model evaluation, optimisation, and performance tuning
• Experience working in cloud environments (Azure, AWS, or GCP)
• Proven ability to work in cross-functional agile teams
• Previous contract or consulting experience in enterprise environments is highly desirable.

Key Skills

• Python (essential)
• ML frameworks (Scikit-learn, TensorFlow, PyTorch)
• Data processing tools (Pandas, NumPy)
• SQL / NoSQL databases
• Cloud platforms (Azure, AWS, GCP)
• Docker, Kubernetes (desirable)
• CI/CD and DevOps tooling

Desirable Experience

• Experience with real-time / streaming ML systems
• Familiarity with Databricks, Spark, or big data platforms
• Exposure to LLMs / Generative AI (RAG, embeddings, etc.)
• Experience with feature stores and modern ML tooling (e.g., Feast)
• Knowledge of AI governance and model explainability
• Industry experience in [Finance / Retail / Healthcare - tailor as needed]

• Opportunity to work on high-impact machine learning projects
• Collaborative and forward-thinking engineering environment
• Flexible working arrangements
• Competitive day rate with extension potential