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Join a Forward-Thinking Data Science Team

Are you a skilled Machine Learning Engineer eager to shape the future of a cutting-edge machine learning operations (MLOps) platform? Join a dynamic, startup-style team within a progressive organisation, where you’ll have the opportunity to build and optimise a cloud-based data science pipeline from the ground up. Based in York or Manchester with a flexible hybrid working model, this role offers the chance to make a significant impact in a fast-paced, AI-driven environment.

About the Role

As a Machine Learning Engineer, you’ll be part of a small, talented team, including one ML Engineer and one Data Scientist, working to deliver innovative AI and machine learning solutions. Reporting to the Lead Data Scientist, you’ll take ownership of the deployment framework for data science services, ensuring seamless integration with a robust data platform. This role is ideal for someone passionate about bridging research and production, with the freedom to define best practices in a setting with minimal legacy constraints. You’ll work on exciting projects involving both generative AI and traditional machine learning, contributing to a transformative data science journey.

Key Responsibilities

• Design and maintain the deployment framework for data science services, overseeing data flow from a central data warehouse into the data science lifecycle.
• Automate critical stages of the data science process, including dataset creation, model training, evaluation, deployment, and monitoring, to ensure scalable, production-ready solutions.
• Collaborate with data scientists, data engineers, and other technical teams to advance the organisation’s analytics capabilities, bridging research and production environments.
• Write high-quality, industry-standard Python code for model training and deployment, adhering to software engineering best practices.
• Troubleshoot networking and connectivity issues between deployed components, leveraging DevOps and networking expertise to ensure platform stability.
• Contribute to data science workflows and discussions, applying machine learning knowledge to address business challenges and deliver actionable insights.
• Exceptional Python programming skills, with a focus on writing clean, maintainable, and high-quality code.
• Strong software engineering expertise, particularly in deploying and maintaining machine learning services in cloud environments.
• Proficiency with Microsoft Azure and Databricks for building and optimising MLOps pipelines, including model deployment and monitoring.
• Solid understanding of DevOps practices and networking fundamentals, with the ability to resolve connectivity challenges post-deployment.
• Experience with test-driven development (e.g., pytest or equivalent), version control systems (VCS), and CI/CD pipelines.
• Ability to identify and apply machine learning solutions to business problems, with a strong grasp of core data science principles.
• A proactive, problem-solving mindset and the agility to thrive in a dynamic environment with shifting priorities and frequent ad-hoc requests.
• Familiarity with other cloud platforms, such as AWS or Google Cloud Platform, though Azure is the primary environment.
• Experience with neural networks, TensorFlow, CatBoost, XGBoost, SKlearn, or Pandas.
• Exposure to Terraform or Infrastructure as Code (IaC), with a willingness to engage with these tools as needed.
• A graduate or postgraduate qualification (or equivalent experience) in a relevant field, such as engineering, mathematics, physics, or statistics.
• Experience in data science within finance, insurance, or e-commerce is advantageous but not required.

Why Join Us?

This is a rare opportunity to join a team with a strong appetite for AI and data science innovation, where you’ll have significant influence over the development of MLOps practices. You’ll work on cutting-edge projects with minimal legacy constraints, collaborating with a supportive team in a culture that values creativity and continuous improvement. The role offers the chance to leave a lasting impact on a growing data science function, with opportunities to work on both generative AI and traditional machine learning initiatives.

About the Team

You’ll join a close-knit team within a newly formed data science function, working on a modern data platform that centralises business data for advanced analytics. The team is focused on building end-to-end data science services, from data acquisition to model deployment, in a collaborative and innovative environment. With a strong emphasis on cross-functional collaboration, you’ll work alongside data scientists, engineers, and other technical specialists to drive impactful outcomes.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

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