Machine Learning Engineer

Experis UK
City of London
4 months ago
Applications closed

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Job Title: Machine Learning Engineer

Location: London, UK (Hybrid – 2–3 days onsite per week)

Contract Type: Contract

Duration: 6–12 months (possibility of extension)

Start Date: ASAP

Overview

We are seeking an experienced Machine Learning Engineer to join our data science and AI engineering team on a contract basis in London. The ideal candidate will be responsible for designing, developing, and deploying machine learning models and scalable data pipelines that support advanced analytics and intelligent automation initiatives.

This role offers a hybrid work arrangement, combining flexibility with collaboration, and is ideal for a contractor who thrives in fast-paced, data-driven environments.

Key Responsibilities

  • Design, build, and deploy machine learning models and AI-driven solutions to address business challenges.
  • Collaborate with data scientists to transition prototypes into production-ready systems.
  • Develop and maintain end-to-end ML pipelines for data ingestion, training, testing, and deployment.
  • Optimise model performance, scalability, and reliability using MLOps best practices.
  • Work with large-scale structured and unstructured datasets for model training and validation.
  • Implement model monitoring, versioning, and retraining processes to ensure continuous improvement.
  • Collaborate cross-functionally with engineering, data, and product teams to integrate ML solutions into production environments.
  • Stay current with emerging trends in AI/ML technologies and contribute to innovation within the organisation.

Required Skills & Experience

  • Proven experience (3–5+ years) as a Machine Learning Engineer, Data Scientist, or similar role.
  • Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy).
  • Solid understanding of machine learning algorithms, statistical modelling, and deep learning architectures.
  • Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI).
  • Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms.
  • Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration.
  • Knowledge of containerization and orchestration tools (Docker, Kubernetes).
  • Experience integrating ML models into production environments via APIs or microservices.
  • Excellent problem-solving, analytical, and communication skills.

Preferred Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, or a related field.
  • Familiarity with CI/CD pipelines for ML model deployment.
  • Exposure to natural language processing (NLP), computer vision, or reinforcement learning projects.
  • Experience working in Agile/Scrum environments.

Contract Details

  • Location: Hybrid – London (onsite 2–3 days per week)
  • Type: Day-rate contract (Outside/Inside IR35 subject to assessment)
  • Duration: 6–12 months (extension likely)
  • Start Date: Immediate or within 2–4 weeks

Why Join

  • Work with a talented, cross-functional AI and data engineering team.
  • Contribute to cutting-edge ML solutions in a collaborative, innovation-driven environment.
  • Hybrid flexibility with a strong London presence.

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