At a Glance
- Tasks: Join a small ML team to scale forecasting systems for frontline organisations.
- Company: Sona, an innovative AI-native workforce management platform.
- Benefits: Competitive salary, share options, 35 days leave, and comprehensive health insurance.
- Other info: Fully remote role with excellent career growth opportunities in a dynamic environment.
- Why this job: Make a real impact on businesses while working with cutting-edge machine learning technology.
- Qualifications: Experience in production ML, strong Python skills, and client-facing deployment experience.
3 billion people across the world work in frontline jobs. 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.
In under 5 years, we've already made a deep impact on the lives of over 100k frontline workers and the operation of their organisations, grown the team to 140+, and secured over $100M in funding from notable VCs, including our Series B led by N47 alongside Felicis, Northzone, and Gradient Ventures (Google). It's a hugely exciting time to be joining the team as we're still small enough that you'll have a significant impact on the company's growth trajectory and culture, yet large enough to have a great structure, experienced leaders and world-class benefits in place.
About the Role
You'll join a two-person ML team that has built a production forecasting system running daily half-hourly predictions across 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. The system works - the challenge now is scaling it from a handful of clients to 100s. 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.
You'll love this role if:
- You enjoy taking ownership of the product and outcome end-to-end.
- 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 have a focus on solving the problem and when given the choice between 'complicated and shiny' vs 'get something simple in front of a user', you choose the latter.
- You're excited by working with our industry experts to really understand what's happening in our client's businesses and the realities of working there.
- 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. You use Claude Code, Cursor, or equivalent daily - not as a novelty, but as your standard working mode.
Our role won't be for you if:
- You're hoping to do research and publish research papers as a key element of the work that you do.
- You're looking to move into a less technical, more managerial role.
- You're keen to get your hands on fancy new technology X and apply it to something.
- You prefer to work on one thing and make it perfect before moving on - the role requires pragmatism, parallelism, and iterative improvement.
Requirements
You'll need these skills/experience to be successful:
- 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 why certain features matter more than model selection, 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.
It would be great if you have experience in some of these areas too:
- Forecasting, time-series, or demand-planning - someone who understands lag features, calendar effects, and evaluation integrity intuitively will ramp significantly faster.
Our stack: Python, scikit-learn, MLflow, Docker, GCP. A small team where ownership is wide and context-switching is normal.
Benefits
- Salary: £95,000-£110,000
- Fully remote (European timezones)
- Share options
- 35 days annual leave (25 days standard plus 10 flexible public holiday days)
- Extra day of leave for every year of service
- Pension contributions matched up to 5%
- Comprehensive health insurance
- Enhanced parental leave
Remote Senior Machine Learning Engineer in Newport employer: Sona
At Sona, we pride ourselves on being an innovative employer that empowers our employees to make a significant impact in the rapidly evolving field of AI-native workforce management. With a fully remote work environment tailored for European timezones, we offer exceptional benefits including 35 days of annual leave, share options, and comprehensive health insurance, all while fostering a collaborative culture that prioritises personal growth and professional development. Join us to be part of a dynamic team where your contributions directly influence the success of frontline organisations and their workers.
StudySmarter Expert Advice🤫
We think this is how you could land Remote Senior Machine Learning Engineer in Newport
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those already working at Sona. A friendly chat can give you insights into the company culture and might even lead to a referral.
✨Tip Number 2
Prepare for those interviews! Brush up on your ML fundamentals and be ready to discuss your past projects. We want to see how you’ve tackled messy data and made decisions under pressure.
✨Tip Number 3
Show us your passion for problem-solving! During interviews, share examples of how you've simplified complex issues or improved processes. We love candidates who focus on practical solutions.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Remote Senior Machine Learning Engineer in Newport
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Senior Machine Learning Engineer role. Highlight your relevant experience in deploying ML systems and client-facing projects, as this will show us you understand what we're looking for.
Showcase Your Skills:Don’t just list your skills; demonstrate them! Use specific examples from your past work where you've successfully used Python and AI tools like Claude Code or Cursor. We want to see how you’ve tackled real-world problems.
Be Personable:Remember, we’re not just looking for a technical whiz; we want someone who can connect with clients too. Share experiences where you’ve built relationships or communicated complex ideas to non-technical stakeholders.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates about the role!
How to prepare for a job interview at Sona
✨Know Your Stuff
Make sure you brush up on your machine learning fundamentals. Be ready to discuss your experience with deploying ML systems, especially in messy data environments. They’ll want to know how you handle unexpected challenges, so have some examples ready!
✨Client-Facing Confidence
Since this role involves client interactions, practice explaining complex concepts in simple terms. Think about how you can convey technical details to non-technical stakeholders without losing them. Role-play with a friend if you need to!
✨Show Your Pragmatism
This position values getting things done over perfection. Prepare to discuss times when you had to make quick decisions or iterate on a project. Highlight your ability to balance quality with speed, especially in a production environment.
✨Familiarise with Their Tools
Get comfortable with the tools mentioned in the job description, like Python and the ML stack. If you’ve used AI development tools like Claude Code or Cursor, be ready to share how they’ve improved your workflow. It shows you’re already aligned with their working style!