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 4 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 110+, and secured over $50M in funding from notable VC’s, including Felicis, Northzone, Gradient Ventures (Google), SpeedInvest, Antler, and Notion Capital, plus notable angels like Tom Blomfield (Monzo).
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. More on working at Sona here.
About the Role
As our new Machine Learning Engineer, you’ll join a small AI/ML team and spearhead the next step of development of Sona’s best-in-industry forecasting models, creating huge impact for our customers. 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 start by solving a well defined forecasting problem, and demonstrating Sona as best in class, then move on to developing green field areas for machine learning and algorithms across the business.
You’ll love this role if:
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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.
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You’re experienced in and excited by taking a future machine learning project from business idea to deployed machine learning system.
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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.
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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.
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You see beyond the data to the world that resulted in this data generating process, the issues that come with this and the opportunity that it gives us.
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You’re happy wearing the many data hats of a startup. You’ll be working with APIs to generate the datasets, doing the data engineering to make them available offline and live, the offline model selection, the live model deployment, monitoring.
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You’re keen to both teach and learn. Explaining your approach to people across the business of varying technical expertise, bringing your deep technical knowledge to offer solutions. At the same time learning from the wealth of expertise in the business to deepen and broaden your skills.
Our role won’t be for you if:
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You’re hoping to do research and publish research papers as a key element of the work that you do.
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You’re looking to move into a less technical, more managerial role soon.
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You’re keen to get your hands on fancy new technology X and apply it to something.
Requirements
You’ll need these skills/experience to be successful:
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Extensive industry ML experience, with a track record of deploying ML systems to production, validating and evaluating them.
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Strong programming skills in Python, including the ML/scientific python stack (e.g. numpy, scikit-learn)
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Strong theoretical understanding of machine learning and how to integrate that machine learning theory with practical decisions.
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Data analysis and technical communication skills. The ability to visualise, communicate and demonstrate your results. (e.g. SQL, pandas, plotting, notebooks)
It would be great if you have experience in some of these areas too:
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Data engineering: building updating datasets from APIs, database design, strong SQL.
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Cloud platforms, containerisation and deployment. Some Docker experience, CI, Git. Familiarity with Google Cloud Platform (GCP) is a plus.
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Building internal APIs (e.g. Flask).
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Algorithms, Operation Research “OR” experience (Python PuLP).
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Online learning / reinforcement learning in a live business setting.
Benefits
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£95-110k (or local currency equivalent)
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Full remote and flexible working (with occasional travel for in-person work)
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Share options
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35 days annual leave (25 days standard plus 10 flexible public holiday days)
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Extra day of leave for every year of service
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Pension contributions matched up to 5%
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Comprehensive health insurance
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Enhanced parental leave & pay
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Co-working space stipend for those based outside London
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Bi-annual all expenses paid team retreats
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The latest Macbook and equipment budget for your home office
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Professional development budget
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Unlimited free books
Note: this represents a typical benefits package for a UK-based, full-time employee. Exact details may vary based on location and employment type but we try to be as fair as possible to all of our team members. Please ask your contact in the Talent team to clarify the available benefits for you.
