Machine Learning Engineer (Agentic AI)
Planday From Xero · UK: London (7 Devonshire Square) ·
- Category
- ML ai
- Experience
- 3+ years
- Company size
- 501-1000
Planday From Xero · UK: London (7 Devonshire Square) ·
HappyRobot · San Francisco
Opendoor · Miami, United States
Build and deploy ML models and agentic AI systems to automate scheduling and workforce management for shift workers, using Python, LLMs, and cloud services.
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.
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.
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.
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.
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.
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.
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