Machine Learning Engineer - AI - MLOps

Posted a week ago by Xpertise Recruitment

Remote job
Location:
Birmingham
Salary/Rate:
£55,000 - £95,000/annum bonus & benefits

Xpertise is seeking two talented Machine Learning Engineers to join our esteemed team in Birmingham. As part of our growing engineering division, you will play a pivotal role in designing, implementing, and optimizing machine learning models and data pipelines. With a strong emphasis on AWS technologies and MLOps practices, you'll have the opportunity to contribute to the development of scalable, production-grade solutions that drive business value.

Key details:

Salary: £(phone number removed) (Mid-Lead)

I'd consider experienced contractors with a rate of £400.00 per day (Outisde IR35)

Benefits: 10-25% bonus + healthcare + 10% pension

Location: Birmingham; can be remote-based, hybrid working or office-based

Key experience desired / what you will learn:

  • Experience developing, deploying, and maintaining machine learning models in production environments.
  • Strong understanding of AWS cloud services, especially in building and managing data pipelines and machine learning workflows: S3, Redshift, Lambda, Glue, EMR, EKS (Kubernetes)
  • Familiarity with MLOps / DevOps concepts and practices, including version control, CI/CD, and model monitoring.
  • Proficiency in Python and relevant data manipulation and analysis libraries (e.g., pandas, NumPy).
  • Experience with distributed computing frameworks like Apache Spark is a plus.
  • Apache Spark and Airflow would be a bonus.

Role overview:

If you're looking to work with a team of ambitious software engineers, talented senior leaders all while working with the latest data, AI and cloud technologies, then this one's for you. They have big plans to disrupt the industry with this machine learning work, so it's a great time to join.

Interested? Please apply with your CV and/or message Billy Hall for further details.

Xpertise acts as an employment agency.

Type:
Permanent
Contract Length:
N/A
Job Reference:
13041
Job ID:
221487135

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