Junior ML DataOps Engineer: Real-Time Data & AI Ops

Kindred (London) Limited; Greater London; On-site; GBP 45,000 - 70,000; Full time

Job summary

FDJ UNITED is seeking a Junior ML DataOps Engineer to help build, operate and improve data tooling and workflows across data science and ML teams. You will contribute to automating processes, improving data quality and testing/monitoring capabilities, while enhancing production reliability and scalability.

You will explore Generative AI and lakehouse tooling, work with cloud-native environments (AWS) and collaborate with engineers to move solutions into production with confidence.

Qualifications

• Good programming skills in Python or Java.
• Understanding of software engineering fundamentals (version control, reviews, testing).
• Interest in DataOps, DevOps, MLOps or ML Engineering and production data systems.
• Familiarity with CI/CD pipelines and automated deployment, or willingness to learn.
• Understanding data pipelines, data processing and data quality.
• Interest in AI/ML, including Generative AI and production challenges.
• Experience with cloud computing, ideally AWS.
• Proactive problem-solving with feedback and learning.
• Good communication and collaboration across teams.
• Growth mindset and willingness to learn new technologies.

Responsibilities

• Build, operate and improve tools, infrastructure and workflows for Data Scientists, Data Engineers and ML Engineers.
• Automate processes, improve data quality, and develop testing and monitoring capabilities.
• Make development and deployment workflows more reliable and efficient.
• Explore and adopt new technologies, including Generative AI, for data products.
• Contribute to Data Lakehouse capabilities and tooling to increase team efficiency.

Tools

Python

Java

AWS

Docker

Kubernetes

Spark

Kafka

Terraform

CloudFormation

Git workflows

CI/CD

Job description

FDJ UNITED is seeking a Junior ML DataOps Engineer to help build, operate and improve data tooling and workflows across data science and ML teams. You will contribute to automating processes, improving data quality and testing/monitoring capabilities, while enhancing production reliability and scalability.

You will explore Generative AI and lakehouse tooling, work with cloud-native environments (AWS) and collaborate with engineers to move solutions into production with confidence.