Machine Learning Engineer

Data Freelance Hub; Remote; GBP 50,000 - 80,000; Full time

Job summary

An innovative freelance platform in the United Kingdom is seeking a Machine Learning Engineer for a contract role. You will design and optimise machine learning models focusing on user personalisation using TensorFlow and GCP. Strong skills in Python, experience with the ML lifecycle, and familiarity with recommender systems are essential. This role offers a competitive pay rate and the opportunity to engage with various teams to deliver cutting-edge ML solutions.

Qualifications

• Extensive experience with the ML lifecycle: model development to deployment.
• Strong proficiency in Python and ML frameworks, especially TensorFlow.
• Hands-on with GCP machine learning services.

Responsibilities

• Design, train, and optimise machine learning models for personalisation.
• Build and maintain scalable data pipelines for model training.
• Deploy ML models to production environments and ensure performance.

Skills

TensorFlow

Python

GCP

A/B Testing

ML Lifecycle Management

Recommender Systems

Deep Learning

Tools

Google Cloud Platform

TensorFlow Serving

TFX

Kubeflow Pipelines

BigQuery

Dataflow

Job description

⭐ - Featured Role | Apply direct with Data Freelance Hub

This role is for a Machine Learning Engineer on a contract basis, offering a competitive pay rate. Key skills include TensorFlow, Python, GCP, and experience with ML lifecycle management. Familiarity with recommender systems and A/B testing is essential.

United Kingdom

#GCP (Google Cloud Platform) #Deep Learning #Python #ML (Machine Learning) #Deployment #Dataflow #Data Processing #Cloud #Batch #PyTorch #Monitoring #AI (Artificial Intelligence) #A/B Testing #Recommender Systems #Datasets #Scala #TensorFlow #Data Pipeline #BigQuery

What you’ll be doing

• Model Development: Design, train, and optimise machine learning models for user personalisation, including recommendation systems, ranking models, user segmentation, and content understanding, with a strong focus on TensorFlow-based development.
• Data Pipeline Engineering: Build and maintain scalable data pipelines to support feature and model training across large structured and unstructured datasets, leveraging cloud‑native tooling.
• Production Deployment: Deploy, monitor, and maintain ML models in production environments, including cloud‑based model serving on GCP. Ensure high availability, strong performance, and continuous model relevance.
• Experimentation: Lead A/B testing and offline experimentation to evaluate model performance and guide ongoing improvement.
• Cross‑Functional Collaboration: Work closely with engineering, product, data, and research teams to ensure ML solutions align with product and business goals.
• Research & Innovation: Stay informed on advances in machine learning, deep learning, and personalisation, and evaluate their integration into existing systems.

What you’ll bring

• End‑to‑end experience across the ML lifecycle: model development, training, deployment, monitoring, and continuous maintenance.
• Strong proficiency in Python and ML frameworks, with expertise in TensorFlow (and experience with PyTorch).
• Experience with GCP machine learning and data services (e.g., Vertex AI, Dataflow, BigQuery, AI Platform, Pub/Sub).
• Hands‑on experience with ML training frameworks such as TFX or Kubeflow Pipelines, and model‑serving technologies like TensorFlow Serving, Triton, or TorchServe.
• Background working with large‑scale batch and real‑time data processing systems.
• Strong understanding of recommender systems, ranking models, and personalisation algorithms.
• Familiarity with Generative AI and its use in production environments.
• Strong communication skills and analytical problem‑solving abilities.

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85 Great Portland Street, London, England, W1W 7LT