Job Description

Senior Machine Learning Engineer - Azure - London - Hybrid - £80k - £110k

My client are a Tier1 law firm who have a vision of becoming the industry leader for innovation using AI and Data Science. This is an incredible opportunity to get in on the ground level of a brand new department where growth and opportunity will come thick and fast.

Role Purpose:

The ML Engineer will be responsible for deploying, managing, and optimizing Large Language Models (LLMs) and other machine learning models within an Azure enterprise data platform.

With a strong focus on the Azure ecosystem, the role will ensure the efficient and cost-effective utilization of cloud resources.

The ML Engineer will help with the development of Data and AI products to accelerate the client's ambition to enhance legal processes through innovative technologies, improve operational efficiency, and deliver data-driven insights for better decision-making.

Responsibilities

Design, develop, and deploy machine learning models using Azure Databricks
Implement and optimize LLMs for various applications, ensuring scalability and performance
Collaborate with DevOps Engineers, data scientists, data engineers, and other stakeholders to integrate ML solutions into production environments
Develop and maintain ETL pipelines to support ML workflows
Monitor and troubleshoot ML models in production, ensuring reliability and accuracy
Stay updated with the latest advancements in ML and LLM technologies and apply them to improve existing solutions
Document processes, models and workflows to ensure knowledge sharing and reproducibility
Leverage their experience with common MLOps frameworks for tracking of experiments, packaging code, and managing model life cycle
Use Terraform for Infrastructure automation

Skills, experience and characteristics:

5+ years of experience in machine learning and data engineering
Proven experience with Azure Databricks and other Azure services (eg, Azure ML, Azure Data Factory)
Experience with Databricks Cluster setup
Experience in leveraging MLflow for experiment tracking, model life cycle management, and versioning of both machine learning and large language models
Knowledge of ETL pipelines (using Azure Data Factory, or Databricks pipelines) to ensure efficient and scalable data flows
Experience with systems like Azure Synapse Analytics for managing large datasets and scaling ML workloads
Expericed in Python, PyTorch, TensorFlow or other DL frameworks
Understanding of Cloud compliance and governance
Deep understanding of primary Azure services (Virtual Machines, Active Directory, Automation)
Experience with containerization and orchestration tools (eg, Docker, Kubernetes)
Experience with version control systems especially Gitlab and CI/CD pipelines
Familiarity with working in an Agile product development environment, including participation in sprint planning, daily stand-ups, and retrospectives
Collegiate attitude with a willingness to support the team's broader goals
Understanding of data structures and transformation logic
Communication skills at the level enabling effective communication across the technical team as well as non-technical teams and stakeholders

This is a hybrid role based in London so candidates must be wiling to work 3 days a week onsite.

Salary range is £80k - £110k plus generous benefits.

If you are interested in this Machine Learning Engineer role based in London please email your CV in the first instance.

Eden Smith are an equal opportunities employer and do not discriminate on any grounds.

Eden Smith Limited

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Senior Machine Learning Engineer - Azure - London - Hybrid - £80k - £110k