Senior Machine Learning Engineer - AI

Yet, despite rising costs and staff shortages, frontline organisations are still left to choose between paper, Excel, and WhatsApp, or decade-old workforce management solutions to take care of the most important part of their businesses - their people.

Enter Sona: the next generation of AI-native, frontline workforce management. We've built an end-to-end platform covering Scheduling, HR, Payroll, and Communications that gives the largest frontline organisations everything they need to staff more intelligently and empower their teams.

You'll join a two-person ML team and a forecasting system making half hourly demand predictions across diverse targets for multiple restaurant chains. Our forecasting models enter into a complex environment with key machine and human decisions being made on their predictions, facing feedback loops and a highly variable environment. You'll own client launches end-to-end: validating data, selecting models, running UAT, going live, and monitoring performance afterwards. You'll join client calls, build relationships, and understand what actually matters on the ground - not just whether the model is accurate, but whether the kitchen prepped the right amount of food.

Machine learning at Sona is a success if we have happy clients running successful businesses as well as the models which are best in industry

You see beyond the data to the world that resulted in this data generating process, the issues that come with it and the opportunity that it gives us

You're experienced in and excited by taking a machine learning project from business idea to deployed production system

You default to AI tools for development and you're excited by what they can achieve for ML. Production ML experience, with a track record of deploying ML systems that handle messy data, fail gracefully, and need monitoring

Strong ML fundamentals - you can reason about trade-offs in practice, explain the "why" behind feature and model choices, and make good judgement calls when something unexpected happens

Client-facing deployment experience - you've personally owned an ML deployment end-to-end and are comfortable on calls with non-technical stakeholders

Strong programming skills in Python, including the ML/scientific Python stack (e.g. numpy, scikit-learn)

Daily use of AI development tools (Claude Code, Cursor, Copilot or equivalent) as your default working mode

Forecasting, time-series, or demand-planning - someone who understands lag features, calendar effects, and evaluation integrity intuitively will ramp significantly faster

Python, scikit-learn, MLflow, Docker, GCP

Fully remote (European timezones)

• 35 days annual leave (25 days standard plus 10 flexible public holiday days)
• Pension contributions matched up to 5%
• Comprehensive health insurance
• Enhanced parental leave & pay
• Salary sacrifice childcare scheme (Workplace Nursery)
• Bi-annual all expenses paid team retreats
• The latest Macbook and equipment budget for your home office
• Professional development budget
• Note: this represents a typical benefits package for a UK-based, full-time employee. Please ask your contact in the Talent team to clarify the available benefits for you.