Senior Machine Learning Engineer

InterQuest Group; United Kingdom; Remote; GBP 80,000 - 100,000; Full time

Job summary

An innovative company is seeking a Senior Machine Learning Engineer to lead the charge in developing advanced time series forecasting solutions. This exciting role involves designing and deploying machine learning models that provide critical insights and drive business value. You will work remotely, collaborating with data scientists and engineers to create robust ML infrastructure and pipelines. If you have a passion for machine learning and a strong background in cloud technologies, this is a fantastic opportunity to make a significant impact in a dynamic and evolving field.

Qualifications

• 5+ years in machine learning solutions in production environments.
• Expertise in AWS SageMaker and cloud-based ML infrastructure.

Responsibilities

• Design and deploy machine learning models using AWS SageMaker.
• Develop scalable ML infrastructure and time series forecasting solutions.

Skills

Machine Learning

Time Series Forecasting

Python Programming

Collaboration

Cloud-based ML Infrastructure

Containerization (Docker)

Infrastructure as Code (AWS CDK)

Tools

AWS SageMaker

AWS CDK

Docker

Job description

Direct message the job poster from InterQuest Group

Data Machine Learning & AI Specialist | Women In Data | Women In Tech

Senior Machine Learning Engineer

Remote working UK or Netherlands

About the Role

As a Senior Machine Learning Engineer, you'll be at the forefront of developing sophisticated time series forecasting solutions that drive business value and market insights.

Key Responsibilities

• Design, develop, and deploy machine learning models using AWS SageMaker
• Create robust, scalable ML infrastructure and pipelines for continuous model training and deployment
• Develop specialized time series forecasting solutions for energy market applications
• Collaborate with data scientists and engineers to translate business requirements into technical solutions

Qualifications

• 5+ years of experience implementing machine learning solutions in production environments
• Demonstrated expertise in AWS SageMaker and broader cloud-based ML infrastructure
• Advanced knowledge of time series forecasting techniques and their practical applications
• Strong proficiency with containerization technologies (Docker)
• Experience with infrastructure-as-code using AWS CDK
• Solid understanding of ML workflow management tools and best practices
• Strong Python programming skills with experience in ML frameworks
• Background in energy markets or similar complex, data-intensive domains preferred

Seniority level: Mid-Senior level

Employment type: Full-time

Job function: Information Technology

Industries: IT Services and IT Consulting