MLOps Engineer - Outside IR35

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

Job summary

A leading insurance broker seeks an ML Ops Engineer to support their Data and AI initiatives. The role involves building and maintaining ML infrastructure, deploying models in Azure Databricks, and collaborating with data teams to optimize platform performance. Ideal candidates will have substantial experience with MLOps, a solid tech stack, and strong analytical skills.

Qualifications

• Experience deploying ML models in Azure Databricks.
• Hands-on development with TensorFlow, PyTorch, and Data Science tools.
• Experience in CI/CD and Agile environments.

Responsibilities

• Implement MLOps pipelines tailored to client needs.
• Collaborate with Data Scientists to enhance features.
• Maintain ML Ops stability and efficiency.

Skills

Machine Learning Infrastructure

Python

Azure

Databricks

CI/CD

Data Science Stack

Tools

Databricks

Azure ML

Git

MLFlow

Delta Tables

Azure DevOps

Job description

An opportunity for an ML Ops Engineer to support a leading Insurancer broker as they embark on the next phase of their Data and AI journey. The successful candidate will have demonstrable experience building and maintaining a robust machine learning infrastructure, supporting the successful deployment and integration of additional AI solutions.

Responsibilities:

• Identify and implement the best approach and practices to MLOps pipelines based on the clients needs.
• Involved in gathering requirements, model registration, performing changes to APIs and models, performing re-deployment tests, handling deploying and making post-deployment checks and maintenance.
• Collaborate with Data Scientists and Platform Engineers to roll out new features and make performance improvements.
• Work with infrastructure as code technology to deploy, manage and run world class MLOps and data solutions
• Maintain strong understanding of Databricks and Azure ML
• Proactively suggest and implement changes to ways of working within and beyond the team to improve platform stability and long term efficiency.
• Ensure smooth day to day running of ML Ops, driving optimisation.
• Share knowledge with the wider data community.

Skills / Attributes / Experience Profile:

• Proven experience deploying and managing ML models in production, in Azure Databricks.
• Tech stack: Databricks, Unity Catalog, Python, Git, MLFlow, Delta tables, Azure DevOps.
• Hands-on development experience using Python, particularly with TensorFlow, PyTorch, scikit-learn, boto3, and the Python Data Science stack (pandas, numpy, etc.).
• Strong analytical and problem-solving skills, with the ability to work with large-scale, complex datasets.
• Experience in automation, CI/CD, and Agile development environments.
• Implementing monitoring for data drift, model drift and performance
• Experience of enabling Feature stores for reusability
• Experience of event driven and / or trigger based applications (real time)
• Experience of upgrading architectures from legacy versions to current versions (i.e. Core Library 2.0 to 3.0, integration of Unity Catalog etc)
• Ability to work independently and within a team.
• Ideally experience working in a consulting / IT Services environment.

Additional Information:

• Location: Home Based, with very occasional travel to Basingstoke
• Rate Offered: £500-550 per day
• IR35 Status: Outside
• Start Date: Start of July
• Initial Duration: 2 Months

Our Client…
…are enabling enterprise customers to take control of their data & AI evolution by combining specialist professional services with talent placement and development for high impact solutions that endure.