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Senior Machine Learning Engineer

JR United Kingdom

Leeds

On-site

GBP 50,000 - 90,000

Full time

8 days ago

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An established industry player is seeking a Senior Machine Learning Engineer to join their innovative team in Leeds. This role focuses on designing and deploying machine learning models and pipelines in production environments, requiring expertise in ML Ops, automation, and cloud integration. You will collaborate with data scientists and engineers to optimize models for scalability and efficiency while ensuring robust documentation of workflows and processes. If you are passionate about advancing machine learning technologies and thrive in a dynamic environment, this opportunity is perfect for you.

Strong foundation in machine learning algorithms and ML Ops practices.
Experience in automating deployment and monitoring of models.

Design and develop machine learning models using various algorithms.
Develop and deploy ML workflows, integrating version control and automation.
Build and maintain end-to-end machine learning pipelines.

Machine Learning

ML Ops

Deep Learning

Data Engineering

Automation

Kubernetes

Python

AWS

Azure

GCP

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Senior Machine Learning Engineer, Leeds, West Yorkshire

Client:

Location:

Leeds, West Yorkshire, United Kingdom

Job Category:

Other

EU work permit required:

Yes

Job Views:

Posted:

13.04.2025

Expiry Date:

28.05.2025

Job Description:

We are looking for a highly skilled Machine Learning Engineer with strong ML Ops expertise to help design, build, deploy, and manage machine learning pipelines in production environments. The ideal candidate will have a strong foundation in machine learning algorithms, deep learning, data engineering, and experience in automating the deployment, monitoring, and scaling of models through ML Ops practices.

Responsibilities:

Model Development: Design and develop machine learning models to solve complex problems using a variety of algorithms, including supervised, unsupervised, and reinforcement learning techniques.
ML Ops Implementation: Develop and deploy ML workflows, integrating version control, automation, and monitoring practices to streamline model development and deployment.
Pipeline Development: Build and maintain end-to-end machine learning pipelines for continuous integration, continuous deployment (CI/CD), and model retraining.
Automation: Automate model training, testing, and deployment processes, ensuring high levels of efficiency and reliability in production.
Model Optimisation: Collaborate with data scientists and engineers to optimise models for production environments, focusing on scalability, speed, and resource efficiency.
Cloud Integration: Utilise cloud platforms (e.g., AWS, Azure, GCP) for model deployment and infrastructure management, ensuring smooth scaling and resource optimisation.
Documentation: Maintain clear and comprehensive documentation for model workflows, ML Ops processes, and system architectures.

Desired Skills and Experience: Software, ML Ops, Kubernetes, Python

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