Machine Learning Engineer (Agentic AI) in London

Machine Learning Engineer (Agentic AI) in London

London Full-Time 63000 - 77000 £ / year (est.) Home office (partial)
Planday From Xero

At a Glance

  • Tasks: Build and optimise ML models to enhance Planday's platform and improve workflows.
  • Company: Join Planday, a leading digital solution for workforce management, part of Xero.
  • Benefits: Enjoy competitive salary, pension, health insurance, and generous vacation.
  • Other info: Flexible remote work, growth opportunities, and a vibrant, inclusive culture.
  • Why this job: Make a real impact on how businesses operate and improve workers' lives.
  • Qualifications: 3-5 years in ML systems, strong Python skills, and collaborative mindset required.

The predicted salary is between 63000 - 77000 £ per year.

Our Purpose Planday from Xero is a leading digital solution that uncomplicates everyday scheduling and workforce management by making it easier for businesses and shift workers around the world to communicate, collaborate, and get work done. Powered by a community of local industry experts, Planday provides a best-in-class digital platform that is easy to use, accurate, secure, and compliant with local needs and standards. From payroll and accounting to POS and reporting, its open API and tech ecosystem is scalable to fit shifting business needs and to build an engaged, flexible workforce. Founded in 2004, Planday is headquartered in Copenhagen, Denmark and supports over 400,000 users across Europe, Australia and the US. Planday was acquired by Xero in 2021.

How you’ll make an impact As a Machine Learning Engineer for Agentic AI & ML, you will work at the intersection of research and production. You will collaborate closely with internal stakeholders and customers to translate ambiguous challenges into effective, shipped features. You will work on features throughout the lifecycle - from discovery and model building to production deployment and maintenance. By designing and shipping ML and agentic systems, you will expand the platform's capabilities to fundamentally reshape how business owners run their operations and how workers manage transparency and work-life balance.

What you’ll do

  • Build and optimize ML models to enhance and extend Planday, framing problems from real metrics and engineering robust feature pipelines.
  • Design and ship agentic systems involving tool use, function calling, and multi-agent orchestration for reliable planning workflows.
  • Deploy and operate model services in production, ensuring performance for cost and latency through caching, batching, and quantization.
  • Design and run rigorous evaluations, including LLM-as-judge and regression suites, so quality changes are always measured.
  • Collaborate on turning research prototypes into reliable, observable production workflows and pipelines.

Success looks like

  • Stable and sustainable support for live ML services in production as our variety of deployments grows.
  • Successful release of new features like auto-scheduler models and intelligent AI agent needs.
  • Reduced ambiguity in model quality through the implementation of repeatable and high-fidelity evaluation sets.
  • Proactive maintenance and debugging of production services, ensuring high reliability for end-users.
  • Delivery of research-backed features that directly improve complex workflows like shift assignment.

What you’ll bring with you

  • 3–5 years of hands-on experience designing, building, and deploying machine learning or data systems in production environments.
  • Strong collaborative skills - we are a small, high-impact team, and we view cross-functional partnership as a feature, not a bug.
  • Solid grounding in ML fundamentals (metrics, validation, leakage) and a strong theoretical foundation in AI research.
  • Practical experience shipping ML or data systems in production environments, beyond purely academic or notebook settings.
  • Strong Python skills, including experience with numerical and dataframe libraries such as NumPy and pandas.
  • Experience writing tested, maintainable, and observable code for services deployed to the cloud.
  • Hands-on experience with LLM applications and agentic architectures, such as RAG, function calling, or planning workflows.
  • Familiarity with data tooling (SQL, dbt, Snowflake/Databricks) and an end-to-end mindset for product building.
  • MSc or equivalent experience in a quantitative field. You combine a strong theoretical foundation with a pragmatic approach, are adept at translating business needs into technical solutions, and actively stay informed on relevant frontier developments.

At Planday, we offer you

  • Benefits like pension, health insurance, inclusive support for new parents and generous vacation.
  • On top of your annual base salary, you are offered to be part of an Employee Share Plan.
  • Growth and progression opportunities – we want you to grow with us.
  • Flexible remote work.
  • Strong social culture with lots of team and company activities.
  • Meaningful work – everyone at Planday contributes to improving the lives of shift workers around the globe.
  • Healthy work-life balance and autonomous approach to work. We trust in you and your abilities.

Finally, our offices are not just workplaces (although they are pretty nice and well-located, we have to say!). Plandayers are open and welcoming and at Planday, everyone has the freedom and support to show their true self at work. At Planday, we firmly believe that diversity and inclusion are the cornerstones of innovation and a vibrant workplace culture. As an equal opportunity employer, we strive to create an equitable experience for all candidates throughout the process. Please let us know if you need any reasonable adjustments during the application or interview process.

Machine Learning Engineer (Agentic AI) in London employer: Planday From Xero

At Planday, we are committed to creating a supportive and inclusive work environment where every employee can thrive. As a Senior Onboarding Consultant, you will enjoy flexible remote work options, generous benefits including health insurance and an Employee Share Plan, and ample opportunities for personal and professional growth. Our vibrant culture fosters collaboration and innovation, ensuring that your contributions make a meaningful impact on the lives of shift workers globally.

Planday From Xero

Contact Details:

Planday From Xero Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Machine Learning Engineer (Agentic AI) in London

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We think you need these skills to ace Machine Learning Engineer (Agentic AI) in London

Machine Learning
Model Building
Production Deployment
Feature Engineering
Python
NumPy
pandas

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Planday From Xero.

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How to prepare for a job interview at Planday From Xero

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Planday From Xero uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

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